[

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/affai","name":"X-ray examinations of atypical femoral fractures","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/affai","author":[{"name":"Jörg Schilcher","@id":"https://orcid.org/0000-0003-0677-9265","@type":"Person"},{"name":"Chunliang Wang","@id":"https://orcid.org/0000-0002-0442-3524","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2021,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Jörg Schilcher","@id":"https://orcid.org/0000-0003-0677-9265","@type":"Person"},{"name":"KTH","url":"https://kth.se/","@type":"Organization"},{"name":"Chunliang Wang","@id":"https://orcid.org/0000-0002-0442-3524","@type":"Person"}],"provider":[{"name":"Jörg Schilcher","email":"jorg.schilcher@liu.se","@id":"https://orcid.org/0000-0003-0677-9265","@type":"Person"},{"name":"Chunliang Wang","email":"chunwan@kth.se","@id":"https://orcid.org/0000-0002-0442-3524","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2021-03-04","datePublished":"2021-03-23","dateModified":"2021-03-23","keywords":"Radiology, X-ray, Annotated, Femur, AFF, Atypical femoral fracture","version":"1.0","description":"Atypical femoral fracture is a well-documented adverse reaction to\nbisphosphonate treatment, but may also have other causes. This dataset contains 433\nradiographs from 149 patients with complete AFF, and 549 radiographs from\n224 patients with normal femur fractures. There are no diagnoses of cancer,\nto reduce the risk of confounding by indication.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/affai#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/affai#aida-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.1080/17453674.2021.1891512","name":"Georg Zdolsek, Yupei Chen, Hans-Peter Bögl, Chunliang Wang, Mischa Woisetschläger & Jörg Schilcher (2021) Deep neural networks with promising diagnostic accuracy for the classification of atypical femoral fractures, Acta Orthopaedica, 92:4, 394-400, DOI: 10.1080/17453674.2021.1891512"}]},
    "other": {"shortName":"AFFAI","origin":"Clinical","status":"Completed","annotation":"Atypical femoral fractures have a characteristic fracture pattern with the\nfracture running perpendicular  to the longitudinal axis of the femur. The\nperiosteal surface shows a focal cortical thickening (attempts to heal the\nfracture) and the fracture extends medially through unaffected cortical bone\nwith a typical medial spike. These three radiographic signs are very typical\nfindings for all kinds of stress fractures in cortical bone.\n\nEach case including radiographs was evaluated by at least one senior\nconsultant in orthopedics, and categorized into atypical femoral fractures\n(AFF) and normal fractures of the femoral shaft (NFF).\n","countries-shared":["IN","SE","US"],"organ":[{"name":"Femur","sctid":71341001}],"age-span":"","bytes":3881258996,"numberOfScans":981,"numberOfAnnotations":981,"resolution":null,"modality":["CR"],"scanner":null,"stain":null,"phase":null,"image":null,"exampleImage":[{"title":"Femur fracture radiograph with an AI generated heatmap indicating probable presence and location of an Atypical Femur Fracture.","url":"/assets/images/10.23698/aida/affai/aff-heatmap.png","thumbnail-url":"/assets/images/10.23698/aida/affai/aff-heatmap-thumbnail.png"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.\nPlease contact the dataset provider for terms of access.</p>\n\n<p>You are invited to send an\n<a href=\"mailto:jorg.schilcher@liu.se?cc=chunwan@kth.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/affai&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Faffai%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Faffai%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">access request email</a>\nfrom your institutional account.</p>\n\n<p>Clicking the access request email link above should open a draft email message\nin a new window, to help you provide relevant information for efficient request\nevaluation. If the above link does not work for you, then please click to view the\n<a id=\"request-email-toggle\">suggested email text</a>.</p>\n\n<div id=\"request-email\" class=\"hidden revealable small\">\n<b>To</b>: jorg.schilcher@liu.se<br />\n<b>cc</b>: chunwan@kth.se,aida-data@nbis.se<br />  \n<b>Subject</b>: Requesting access to dataset doi:10.23698/aida/affai<br />\nHi!<br />\n<br />\nI work at INSTITUTION in COUNTRY, emailing from my institutional account.<br />\n<br />\nI would like to access the dataset doi:10.23698/aida/affai, for use in ethical and legal medical diagnostics research. Could you please send me a data sharing agreement template?<br />\n<br />\nOur planned use of the data can be summarized as:<br />\n<br />\nBRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES<br />\n<br />\nDataset: https://datahub.aida.scilifelab.se/10.23698/aida/affai<br />\n<br />\nExample agreement template: https://datahub.aida.scilifelab.se/sharing/templates/<br />\n<br />\nTemplate placeholders:<br />\n<br />\nResearch PI (\"Recipient Scientist\"):<br />\nName: PI_NAME (cc here)<br />\nTitle: PI_TITLE (ph d or better, in relevant field)<br />\n<br />\nName of institution: INSTITUTION_NAME<br />\nName of department: DEPARTMENT_NAME<br />\nInstitution postal address: POSTAL_ADDRESS<br />\n<br />\nAuthorized signatory (if other than research PI):<br />\nName: SIGNATORY_NAME (cc here)<br />\nTitle: SIGNATORY_TITLE<br />\n<br />\nThe Research PI has a PhD degree or better in a relevant field, and their institutional email address is in CC in this email conversation. The Authorized signatory is the person who signs this type of legal agreement on behalf of this institution, and their institutional email address is in CC in this conversation.<br />\n<br />\n/MY_NAME<br />\n<br />\nClick to <a href=\"mailto:jorg.schilcher@liu.se?cc=chunwan@kth.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/affai&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Faffai%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Faffai%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">create draft email</a> (new window). Use your institutional account.\n</div>\n<script>\ndocument.querySelector(\"#request-email-toggle\").addEventListener('click', (e) => {\n  document.querySelector(\"#request-email\").classList.toggle('hidden')\n  })\n</script>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2021\nLinköping University, Jörg Schilcher, KTH, Chunliang Wang</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the purpose\nof medical diagnostics research with or without fee is hereby granted, provided that\nthe above copyright notice and this permission notice appear in all copies, and that\npublications resulting from the use of this data cite the following works:</p>\n\n<p>Jörg Schilcher and Chunliang Wang\n(2021)\nX-ray examinations of atypical femoral fractures\n<a href=\"https://doi.org/10.23698/aida/affai\">doi:10.23698/aida/affai</a>.</p>\n\n<p><a href=\"https://doi.org/10.1080/17453674.2021.1891512\">Georg Zdolsek, Yupei Chen, Hans-Peter Bögl, Chunliang Wang, Mischa Woisetschläger &amp; Jörg Schilcher (2021) Deep neural networks with promising diagnostic accuracy for the classification of atypical femoral fractures, Acta Orthopaedica, 92:4, 394-400, DOI: 10.1080/17453674.2021.1891512</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/anklefx","name":"Annotated radiographs of ankle fractures for research","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/anklefx","author":[{"name":"Jakub Olczak","@type":"Person"},{"name":"Filip Emilson","@type":"Person"},{"name":"Ali Razavian","@type":"Person"},{"name":"Tone Antonsson","@type":"Person"},{"name":"Andreas Stark","@type":"Person"},{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2021,"copyrightHolder":[{"name":"Karolinska Institutet","url":"https://ki.se/","@type":"Organization"},{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"provider":[{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"},{"name":"Max Gordon","email":"max.gordon@ki.se","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"dateCreated":"2024-11-29","datePublished":"2024-11-29","dateModified":"2024-11-29","keywords":"Ankle fractures, Radiology, Annotations, Medical imaging, AO/OTA","version":"1.0.0","description":"The Ankle Fracture dataset includes radiological images for diagnosing and evaluating ankle fractures. The dataset focuses on X-ray imaging, providing annotations for fracture identification, classification, and severity grading.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/anklefx#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/anklefx#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.1186/s12891-024-07884-2","name":"Olczak J, Prijs J, IJpma F, Wallin F, Akbarian E, Doornberg J, et al. External validation of an artificial intelligence multi-label deep learning model capable of ankle fracture classification. BMC Musculoskelet Disord. 2024 Oct 4;25(1):788."},{"@type":"CreativeWork","@id":"https://doi.org/10.1080/17453674.2020.1837420","name":"Olczak J, Emilson F, Razavian A, Antonsson T, Stark A, Gordon M. Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification. Acta Orthopaedica. 2021 Jan 2;92(1):102–8."}]},
    "other": {"shortName":"ANKLEFX","origin":"Clinical","status":"Completed","annotation":"Annotations are manually created and validated by clinical experts, including fracture classification, severity grading, and localization markers on X-rays.\n","countries-shared":["SE"],"organ":[{"name":"Ankle","sctid":344001}],"age-span":"15+","bytes":3224194682,"numberOfScans":1751,"numberOfAnnotations":400,"resolution":"","modality":["CR"],"scanner":null,"stain":null,"phase":null,"image":"/assets/images/10.23698/aida/anklefx/img1_thumbnail.png","exampleImage":[{"title":"","url":"/assets/images/10.23698/aida/anklefx/img1.png","thumbnail-url":"/assets/images/10.23698/aida/anklefx/img1_thumbnail.png"},{"title":"","url":"/assets/images/10.23698/aida/anklefx/img2.png","thumbnail-url":"/assets/images/10.23698/aida/anklefx/img2_thumbnail.png"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/anklefx\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2021\nKarolinska Institutet, Max Gordon</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Jakub Olczak, Filip Emilson, Ali Razavian, Tone Antonsson, Andreas Stark, and Max Gordon\n(2024)\nAnnotated radiographs of ankle fractures for research\n<a href=\"https://doi.org/10.23698/aida/anklefx\">doi:10.23698/aida/anklefx</a>.</p>\n\n<p><a href=\"https://doi.org/10.1186/s12891-024-07884-2\">Olczak J, Prijs J, IJpma F, Wallin F, Akbarian E, Doornberg J, et al. External validation of an artificial intelligence multi-label deep learning model capable of ankle fracture classification. BMC Musculoskelet Disord. 2024 Oct 4;25(1):788.</a></p>\n\n<p><a href=\"https://doi.org/10.1080/17453674.2020.1837420\">Olczak J, Emilson F, Razavian A, Antonsson T, Stark A, Gordon M. Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification. Acta Orthopaedica. 2021 Jan 2;92(1):102–8.</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/bccc","name":"Basal cell carcinoma classification","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/bccc","author":[{"name":"Noora Neittaanmäki","@id":"https://orcid.org/0000-0002-8733-5510","@type":"Person"},{"name":"Kajsa Villiamsson","@id":"https://orcid.org/0000-0002-9338-5098","@type":"Person"},{"name":"Jan Siarov","@id":"https://orcid.org/0000-0002-2013-3113","@type":"Person"},{"name":"Filmon Yacob","@id":"https://orcid.org/0000-0003-3283-5670","@type":"Person"},{"name":"Juulia T Suvilehto","@id":"https://orcid.org/0000-0003-3882-1069","@type":"Person"},{"name":"Lisa Sjöblom","@id":"https://orcid.org/0000-0003-3381-1232","@type":"Person"},{"name":"Magnus Kjellberg","@id":"https://orcid.org/0000-0002-6921-8257","@type":"Person"},{"name":"John Paoli","@id":"https://orcid.org/0000-0003-1326-8535","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2023,"copyrightHolder":[{"name":"University of Gothenburg","url":"https://www.gu.se/","@type":"Organization"},{"name":"Noora Neittaanmäki","@id":"https://orcid.org/0000-0002-8733-5510","@type":"Person"}],"provider":[{"name":"Noora Neittaanmäki","email":"noora.neittaanmaki@vgregion.se","@id":"https://orcid.org/0000-0002-8733-5510","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2023-03-02","datePublished":"2023-03-17","dateModified":"2023-03-17","keywords":"Pathology, Whole slide imaging, Weakly annotated, Basal cell carcinoma, Skin cancer","version":"1.0.2","description":"Whole slide pathology images from cutaneous basal cell carcinomas (BCC) specimens collected at the Department of Pathology at Sahlgrenska University Hospital, Sweden. All whole slide images (WSI) are annotated on a slide level. The dataset contains:\n\n- 1832 WSIs from 479 excised BCCs.\n- 261 WSIs from punch biopsies representing BCCs and 253 WSIs from tumor-free skin biopsies.\n- 995 WSIs from frozen Mohs micrographic surgery.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/bccc#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/bccc#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution and co-authorship."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.1038/s41598-023-33863-z","name":"Yacob, F., Siarov, J., Villiamsson, K. et al. Weakly supervised detection and classification of basal cell carcinoma using graph-transformer on whole slide images. Sci Rep 13, 7555 (2023). https://doi.org/10.1038/s41598-023-33863-z"},{"@type":"CreativeWork","@id":"https://doi.org/10.1186/s12880-025-01710-4","name":"Björkman, J., Lagerroth, S., Siarov, J. et al. Enhancing basal cell carcinoma classification in preoperative biopsies via transfer learning with weakly supervised graph transformers. BMC Med Imaging 25, 166 (2025). https://doi.org/10.1186/s12880-025-01710-4"},{"@type":"CreativeWork","@id":"https://doi.org/10.1016/j.jdin.2026.07.004","name":"Kajsa Villiamsson, Ludvig Forndstedt, Geert Litjens, Nelli Sjöblom, Olivia Vesala, Filmon Yacob, John Paoli, Noora Neittaanmäki. Detection of Basal Cell Carcinoma on Whole-slide Images from Mohs Micrographic Surgery Using Weakly Supervised Learning. JAAD International 2026; 28,76-85.  https://doi.org/10.1016/j.jdin.2026.07.004"}]},
    "other": {"shortName":"BCCC","origin":"Clinical","status":"Completed","annotation":"The data is annotated on a slide level into four aggressivity tumour subtypes: low aggressive Ia (nodular) and Ib (superficial) and more aggressive subtypes II (medium aggressive) and III (high aggressive). Of these, types Ia and Ib represent low risk and II and III high risk tumors according to WHO classilification of skin tumors (4th Edition 2018).\n","countries-shared":["BD","CA","CN","DZ","FR","IR","IN","JO","NL","PK","SE","US"],"organ":[{"name":"Skin","sctid":39937001}],"age-span":"-","bytes":11218034260000,"numberOfScans":2827,"numberOfAnnotations":0,"resolution":"x40","modality":["SM"],"scanner":["NanoZoomer S360 Hamamatsu"],"stain":"H&E (hematoxylin and eosin)","phase":null,"image":"/assets/images/10.23698/aida/bccc/sample1-thumbnail.jpeg","exampleImage":[{"title":"Sample image 1","url":"/assets/images/10.23698/aida/bccc/sample1.jpeg","thumbnail-url":"/assets/images/10.23698/aida/bccc/sample1-thumbnail.jpeg"},{"title":"Sample image 2","url":"/assets/images/10.23698/aida/bccc/sample2.jpeg","thumbnail-url":"/assets/images/10.23698/aida/bccc/sample2-thumbnail.jpeg"},{"title":"Sample image 3","url":"/assets/images/10.23698/aida/bccc/sample3.jpeg","thumbnail-url":"/assets/images/10.23698/aida/bccc/sample3-thumbnail.jpeg"},{"title":"Sample image 4","url":"/assets/images/10.23698/aida/bccc/sample4.jpeg","thumbnail-url":"/assets/images/10.23698/aida/bccc/sample4-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of two types of images:\nHistopathological slides are stored as .ndpi (size per slide 1-5.5GB).\nAnnotations are provided as .csv files (one for main data set, one for test set)</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/bccc\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2023\nUniversity of Gothenburg, Noora Neittaanmäki</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the purpose\nof medical diagnostics research with or without fee is hereby granted, provided that\nthe above copyright notice and this permission notice appear in all copies, and that\npublications resulting from the use of this data cite the following works:</p>\n\n<p>Noora Neittaanmäki, Kajsa Villiamsson, Jan Siarov, Filmon Yacob, Juulia T Suvilehto, Lisa Sjöblom, Magnus Kjellberg, and John Paoli\n(2023)\nBasal cell carcinoma classification\n<a href=\"https://doi.org/10.23698/aida/bccc\">doi:10.23698/aida/bccc</a></p>\n\n<p><a href=\"https://doi.org/10.1038/s41598-023-33863-z\">Yacob, F., Siarov, J., Villiamsson, K. et al. Weakly supervised detection and classification of basal cell carcinoma using graph-transformer on whole slide images. Sci Rep 13, 7555 (2023). https://doi.org/10.1038/s41598-023-33863-z</a></p>\n\n<p><a href=\"https://doi.org/10.1186/s12880-025-01710-4\">Björkman, J., Lagerroth, S., Siarov, J. et al. Enhancing basal cell carcinoma classification in preoperative biopsies via transfer learning with weakly supervised graph transformers. BMC Med Imaging 25, 166 (2025). https://doi.org/10.1186/s12880-025-01710-4</a></p>\n\n<p><a href=\"https://doi.org/10.1016/j.jdin.2026.07.004\">Kajsa Villiamsson, Ludvig Forndstedt, Geert Litjens, Nelli Sjöblom, Olivia Vesala, Filmon Yacob, John Paoli, Noora Neittaanmäki. Detection of Basal Cell Carcinoma on Whole-slide Images from Mohs Micrographic Surgery Using Weakly Supervised Learning. JAAD International 2026; 28,76-85.  https://doi.org/10.1016/j.jdin.2026.07.004</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/brln","name":"Axillary lymph nodes in breast cancer cases","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/brln","author":[{"name":"Sofia Jarkman","@type":"Person"},{"name":"Martin Lindvall","@id":"https://orcid.org/0000-0002-7014-8874","@type":"Person"},{"name":"Joel Hedlund","@id":"https://orcid.org/0000-0001-6443-3604","@type":"Person"},{"name":"Darren Treanor","@id":"https://orcid.org/0000-0002-4579-484X","@type":"Person"},{"name":"Claes Lundstrom","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Jeroen van der Laak","@id":"https://orcid.org/0000-0001-7982-0754","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Claes Lundström","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"provider":[{"name":"Claes Lundstrom","email":"claes.lundstrom@liu.se","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Sofia Jarkman","email":"sofia.jarkman@regionostergotland.se","@type":"Person"},{"name":"Joel Hedlund","email":"joel.hedlund@liu.se","@id":"https://orcid.org/0000-0001-6443-3604","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2019-11-19","datePublished":"2019-11-19","dateModified":"2019-11-21","keywords":"Pathology, Whole slide imaging, Breast, Lymph nodes, Cancer, Sentinel nodes, Immunohistochemical staining, cytokeratin, CKAE1/AE3","version":"1.0.2","description":"Whole slide imaging of 396 full cases of axillary lymph nodes in breast cancer cases. Included are both sentinel node surgery and axillary dissections pre, peri or post breast cancer surgery or treatment. Sentinel node cases are cut in three levels (stained with HE) and one additional slide immunohistochemically stained with CKAE1/AE3. The number of sentinel node cases with complete immunohistochemical staining is 321. The axillary dissections are cut with one cut level as default. No frozen sections included. The cases are anonymised and exported from the digital archive at the Department of Clinical Pathology in Linköping, Region Östergötland. Included are both positive and negative cases. Some metadata on case level is available (positive or negative case, number of nodes, primary tumour and if neoadjuvant treatment in axillary dissections was given).\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/brln#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY CA license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/brln#aida-by-ca-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution and co-authorship."}],"citation":null},
    "other": {"shortName":"BRLN","origin":"Clinical","status":"Ongoing","annotation":"No in-image annotations available.\n","countries-shared":["CN","FI","KR","NL","NO","SE","US"],"organ":[{"name":"Breast","sctid":76752008}],"age-span":"-","bytes":2363159897649,"numberOfScans":4462,"numberOfAnnotations":0,"resolution":"20x","modality":["SM"],"scanner":["Aperio ScanScope AT","Hamamatsu NanoZoomer XR","Hamamatsu NanoZoomer S360","Hamamatsu NanoZoomer S60"],"stain":"Hematoxylin and eosin. In sentinel node cases also immunohistochemical stain  for cytokeratin AE1/AE3.","phase":null,"image":"/assets/images/10.23698/aida/brln/ckae-metastasis-thumbnail.jpeg","exampleImage":[{"title":"Overview of whole slide imaging with hematoxylin and eosin staining.","url":"/assets/images/10.23698/aida/brln/he-overview.jpeg","thumbnail-url":"/assets/images/10.23698/aida/brln/he-overview-thumbnail.jpeg"},{"title":"Overview of whole slide imaging with cytokeratin immunostaining.","url":"/assets/images/10.23698/aida/brln/ckae-overview.jpeg","thumbnail-url":"/assets/images/10.23698/aida/brln/ckae-overview-thumbnail.jpeg"},{"title":"Detail view of metastasis with hematoxylin and eosin staining.","url":"/assets/images/10.23698/aida/brln/he-metastasis.jpeg","thumbnail-url":"/assets/images/10.23698/aida/brln/he-metastasis-thumbnail.jpeg"},{"title":"Detail view of metastasis with cytokeratin immunostaining.","url":"/assets/images/10.23698/aida/brln/ckae-metastasis.jpeg","thumbnail-url":"/assets/images/10.23698/aida/brln/ckae-metastasis-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<h3 id=\"pixel-position-scaling\">Pixel position scaling</h3>\n<p>Coordinates given are relative to the image <em>width</em>. To get the correct pixel\nposition, X coordinates (and Y coordinates!) should therefore be multiplied with\nthe image <em>width</em>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/brln\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-ca-license\">AIDA BY CA license</h3>\n<p>Copyright\n2019\nLinköping University, Claes Lundström</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the following works:</p>\n\n<p>Sofia Jarkman, Martin Lindvall, Joel Hedlund, Darren Treanor, Claes Lundstrom, and Jeroen van der Laak\n(2019)\nAxillary lymph nodes in breast cancer cases\n<a href=\"https://doi.org/10.23698/aida/brln\">doi:10.23698/aida/brln</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/brmbr","name":"Breast data from preoperative and surgical cases","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/brmbr","author":[{"name":"Anna Bodén","@id":"https://orcid.org/0000-0002-0128-870X","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2023,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Claes Lundström","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"provider":[{"name":"Claes Lundstrom","email":"claes.lundstrom@liu.se","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Anna Bodén","email":"Anna.C.Boden@regionostergotland.se","@id":"https://orcid.org/0000-0002-0128-870X","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2023-02-15","datePublished":"2023-05-24","dateModified":"2023-05-15","keywords":"Breast cancer, Pathology, Whole slide imaging","version":"1.0.1","description":"Whole slide imaging of 102 primary diagnosed breast cancers. In this dataset one representative image from the preoperative biopsy have been manually selected and matched with one image representative from the surgically removed invasive tumour. Both biopsy and whole section are presented as one case and contain 2 HE stained slides per case. The section from the surgical resection is from one piece as default, biopsies may vary from 1-3 per slide. Breastcancer cases were consecutively selected from the laboratory information system based on diagnosis including only Invasive breast cancer (NST) and Invasive lobular carcinoma (ILC). Each slide has been evaluated in clinic by at least one senior consultant in breast pathology and controlled before extraction to this dataset by an additional independent senior breast pathologist. No neoadjuvant cases included. No male breast cancers included. The cases are anonymised and exported from the digital archive at the Department of Clinical Pathology in Linköping, Region Östergötland.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/brmbr#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/brmbr#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":null},
    "other": {"shortName":"BRMBR","origin":"Clinical","status":"Ongoing","annotation":"No in-image annotations available.\n","countries-shared":["FR","NL","US"],"organ":[{"name":"Breast","sctid":76752008}],"age-span":null,"bytes":120259084288,"numberOfScans":102,"numberOfAnnotations":0,"resolution":"x40 (one large section x20 is included)","modality":["SM"],"scanner":["Hamamatsu NanoZoomer XR","Hamamatsu NanoZoomer S360","Hamamatsu NanoZoomer S60"],"stain":"H&E (hematoxylin and eosin)","phase":null,"exampleImage":[{"title":"Example from case 11 in this dataset, here showing the preoperative sample (biopsy) in low resolution, that is paired on case level with an image from the surgical specimen from the aligned breastcancer.","url":"/assets/images/10.23698/aida/brmbr/11A.jpg","thumbnail-url":"/assets/images/10.23698/aida/brmbr/11A-thumbnail.jpg"},{"title":"A close up in high resolution from Figure 1; an example from case 11 in this dataset, here showing an area of interest for atypia and mitosis from the preoperative sample (biopsy).","url":"/assets/images/10.23698/aida/brmbr/11A_high resolution on biopsy.jpg","thumbnail-url":"/assets/images/10.23698/aida/brmbr/11A_high resolution on biopsy-thumbnail.jpg"},{"title":"Example from case 11 in this dataset, here showing the chosen image from the surgical sample (excision) in low resolution, that is paired on case level with an image of the preoperative biopsy from the same breastcancer","url":"/assets/images/10.23698/aida/brmbr/11B.jpg","thumbnail-url":"/assets/images/10.23698/aida/brmbr/11B-thumbnail.jpg"},{"title":"A close up in high resolution from Figure 3; an example from case 11 in this dataset, here showing an area of interest for atypia and mitosis from the preoperative sample (biopsy).","url":"/assets/images/10.23698/aida/brmbr/11B_high resolution on resection slide.jpg","thumbnail-url":"/assets/images/10.23698/aida/brmbr/11B_high resolution on resection slide-thumbnail.jpg"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/brmbr\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2023\nLinköping University, Claes Lundström</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Anna Bodén\n(2023)\nBreast data from preoperative and surgical cases\n<a href=\"https://doi.org/10.23698/aida/brmbr\">doi:10.23698/aida/brmbr</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/ctpa","name":"Computed Tomography Pulmonary Angiography (CTPA) data","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/ctpa","author":[{"name":"Tobias Sjöblom","@id":"https://orcid.org/0000-0001-6668-4140","@type":"Person"},{"name":"Nataša Sladoje","@id":"https://orcid.org/0000-0002-6041-6310","@type":"Person"},{"name":"Ali Teymur Kahraman","@id":"https://orcid.org/0000-0001-7488-6105","@type":"Person"},{"name":"Dimitris Toumpanakis","@type":"Person"},{"name":"Tomas Fröding","@id":"https://orcid.org/0000-0002-4053-4301","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Uppsala University","url":"https://uu.se/","@type":"Organization"},{"name":"Tobias Sjöblom","@id":"https://orcid.org/0000-0001-6668-4140","@type":"Person"},{"name":"Nyköpings Lasarett","url":"Axial CTPA image showing annotated pulmonary emboli","@type":"Organization"},{"name":"Tomas Fröding","@id":"https://orcid.org/0000-0002-4053-4301","@type":"Person"}],"provider":[{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"},{"name":"Tomas Fröding","email":"tomaskjfroding@gmail.com","@id":"https://orcid.org/0000-0002-4053-4301","@type":"Person"}],"dateCreated":"2019-04-08","datePublished":"2019-04-08","dateModified":"2019-04-00","keywords":"Radiology, Computed tomography, Thorax, Pulmonary embolism, Annotated","version":"1.0","description":"30 clinical routine CTPA examinations, performed on a Philips Brilliance 64\nCT or GE Lightspeed VCT. 14317 axial images (1 or 0,625mm) plus additional\nreformats. 5 of the CTPAs are positive for pulmonary embolism and have all\nthe emboli carefully delineated by an experienced radiologist.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/ctpa#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/ctpa#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution and co-authorship."}],"citation":null},
    "other": {"shortName":"CTPA","origin":"Clinical","status":"Ongoing","annotation":"All pulmonary emboli have been delineated by an experienced radiologist - in\nan image by image process (in axial view 1 or 0,625mm images) using MITK\nWorkbench. 1 283 annotations were made, in a total of 38 emboli.\n","countries-shared":["BE","DE","IL","IN","JO","LK","SE","US"],"organ":[{"name":"Lung","sctid":39607008}],"age-span":"45-93","bytes":4500000000,"numberOfScans":30,"numberOfAnnotations":1283,"resolution":null,"modality":["CT"],"scanner":["Philips Brilliance 64 CT","GE Lightspeed VCT"],"stain":null,"phase":"Contrast enhanced, pulmonary arterial phase","image":"/assets/images/10.23698/aida/ctpa/axial-ctpa-annotated-thumbnail.jpg","exampleImage":[{"title":"3D volume rendered image.","url":"/assets/images/10.23698/aida/ctpa/3d.jpg","thumbnail-url":"/assets/images/10.23698/aida/ctpa/3d-thumbnail.jpg"},{"title":"Axial CTPA image showing pulmonary emboli.","url":"/assets/images/10.23698/aida/ctpa/axial-ctpa.jpg","thumbnail-url":"/assets/images/10.23698/aida/ctpa/axial-ctpa-thumbnail.jpg"},{"title":"Axial CTPA image with annotated pulmonary emboli.","url":"/assets/images/10.23698/aida/ctpa/axial-ctpa-annotated.jpg","thumbnail-url":"/assets/images/10.23698/aida/ctpa/axial-ctpa-annotated-thumbnail.jpg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>DICOM. Please see our help pages for some examples of\n<a href=\"https://docs.datahub.aida.scilifelab.se/data/working-with-dicom/\">working with DICOM</a>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/ctpa\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2019\nUppsala University, Tobias Sjöblom, Nyköpings Lasarett, Tomas Fröding</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the following works:</p>\n\n<p>Tobias Sjöblom, Nataša Sladoje, Ali Teymur Kahraman, Dimitris Toumpanakis, and Tomas Fröding\n(2019)\nComputed Tomography Pulmonary Angiography (CTPA) data\n<a href=\"https://doi.org/10.23698/aida/ctpa\">doi:10.23698/aida/ctpa</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/ctpel","name":"Segmented CT pelvis scans with annotated anatomical landmarks","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/ctpel","author":[{"name":"Bryan Connolly","@type":"Person"},{"name":"Chunliang Wang","@id":"https://orcid.org/0000-0002-0442-3524","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"KTH","url":"https://kth.se/","@type":"Organization"},{"name":"Chunliang Wang","@id":"https://orcid.org/0000-0002-0442-3524","@type":"Person"}],"provider":[{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"},{"name":"Chunliang Wang","email":"chunwan@kth.se","@id":"https://orcid.org/0000-0002-0442-3524","@type":"Person"}],"dateCreated":"2019-05-03","datePublished":"2019-05-03","dateModified":"2021-06-24","keywords":"Radiology, Annotated, Pelvis, CT, Computed tomography, Anatomical landmarks, Bone segmentation","version":"1.1","description":"5 bone segmentation masks and 15 annotations of anatomical landmarks for pelvis bones\nin each of 90 Computed Tomography (CT) cases extracted from the\n[CT Lymph nodes](https://wiki.cancerimagingarchive.net/display/Public/CT+Lymph+Nodes) and\n[CT Colonography](https://wiki.cancerimagingarchive.net/display/Public/CT+COLONOGRAPHY)\ncollections from the\n[The Cancer Imaging Archive](https://www.cancerimagingarchive.net/) (TCIA).\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/ctpel#controlled-access","@type":"CreativeWork","abstract":"Free for use in research or education.\n"},{"name":"AIDA license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/ctpel#aida-license","@type":"CreativeWork","abstract":"Free for use within AIDA."}],"citation":[{"@type":"Chapter","@id":"https://doi.org/10.1007/978-3-030-11166-3_5","name":"Wang C., Connolly B., de Oliveira Lopes P.F., Frangi A.F., Smedby Ö.\n(2019) Pelvis Segmentation Using Multi-pass U-Net and Iterative Shape\nEstimation. In: Vrtovec T., Yao J., Zheng G., Pozo J. (eds)\nComputational Methods and Clinical Applications in Musculoskeletal\nImaging. MSKI 2018. Lecture Notes in Computer Science, vol 11404.\nSpringer, Cham\n"}]},
    "other": {"shortName":"CTPEL","origin":"Clinical","status":"Ongoing","annotation":"Segmentation was done first with an interactive software (Mialab), followed\nby manual inspection and correction using ITKSNAP. The interactive method is\nbased on fuzzy connectedness followed by level set method. Both the\nsegmentation mask and annotated anatomical landmarks were created by a\ntrained radiologist.\n","countries-shared":["AU","BE","BR","CA","CH","CN","DE","DK","EG","ES","FR","GB","IN","IL","IR","JP","KR","NL","NO","PL","RO","SE","TR","US","VN"],"organ":[{"name":"Pelvis","sctid":12921003}],"age-span":"","bytes":28000000000,"numberOfScans":90,"numberOfAnnotations":1800,"resolution":null,"modality":["CT"],"scanner":null,"stain":null,"phase":null,"image":null,"exampleImage":[{"title":"Anatomical landmarks of pelvis and femur indicated in a 3d volume rendered image.","url":"/assets/images/10.23698/aida/ctpel/landmarks.png","thumbnail-url":"/assets/images/10.23698/aida/ctpel/landmarks-thumbnail.png"},{"title":"Segmentation masks for femur, pelvis, and vertebra shown in a frontal plane CT image.","url":"/assets/images/10.23698/aida/ctpel/segmentations.png","thumbnail-url":"/assets/images/10.23698/aida/ctpel/segmentations-thumbnail.png"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>DICOM. Please see our help pages for some examples of\n<a href=\"https://docs.datahub.aida.scilifelab.se/data/working-with-dicom/\">working with DICOM</a>.</p>\n\n<h3 id=\"importing-binary-masks-to-numpy\">Importing binary masks to numpy</h3>\n<p>The dataset contains a DICOM SEG file, which can be converted to an ITK image file (mha, nifti, etc) by using <a href=\"https://github.com/QIICR/dcmqi\">dcmqi</a> and the command line tool <a href=\"https://qiicr.gitbook.io/dcmqi-guide/opening/cmd_tools/seg/segimage2itkimage\">segimage2itkimage</a>, which is straightforward to read into a numpy array.</p>\n\n<h3 id=\"landmarks\">Landmarks</h3>\n<p>Landmarks are available in the sr.dcm file and saved using the TID 1500 template.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in research or education.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/ctpel\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<h4 id=\"segmentation-masks-and-anatomical-landmark-annotations\">Segmentation masks and anatomical landmark annotations</h4>\n<p>Copyright\n2019\nKTH, Chunliang Wang</p>\n\n<p>Permission to use, copy, modify, and/or distribute the data within AIDA\n(Analytic Imaging Diagnostics Arena https://medtech4health.se/aida) for the\npurpose of research or education with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n\n<h2 id=\"attribution\">Attribution</h2>\n<p>In addition to the TCIA rules about using the image data, we would really\nappreciate if you include the following references in publications that make use\nof the provided segmentation masks or anatomical landmarks:</p>\n\n<p>[1] Bryan Connolly and Chunliang Wang\n(2019)\nSegmented CT pelvis scans with annotated anatomical landmarks\n<a href=\"https://doi.org/10.23698/aida/ctpel\">doi:10.23698/aida/ctpel</a>.</p>\n\n<p>[2]\n  <a href=\"https://doi.org/10.1007/978-3-030-11166-3_5\">Wang C., Connolly B., de Oliveira Lopes P.F., Frangi A.F., Smedby Ö.\n(2019) Pelvis Segmentation Using Multi-pass U-Net and Iterative Shape\nEstimation. In: Vrtovec T., Yao J., Zheng G., Pozo J. (eds)\nComputational Methods and Clinical Applications in Musculoskeletal\nImaging. MSKI 2018. Lecture Notes in Computer Science, vol 11404.\nSpringer, Cham\n</a></p>\n\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/ctskull","name":"CT of normal skulls in three categories (Female, Male, Mixed)","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/ctskull","author":[{"name":"Einar Heiberg","@id":"https://orcid.org/0000-0003-2848-3326","@type":"Person"},{"name":"Finn Lennartsson","@id":"https://orcid.org/0000-0003-1110-8896","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2021,"copyrightHolder":[{"name":"Lund University","url":"https://www.lunduniversity.lu.se/","@type":"Organization"},{"name":"Einar Heiberg","@id":"https://orcid.org/0000-0003-2848-3326","@type":"Person"}],"provider":[{"name":"Einar Heiberg","email":"einar.heiberg@med.lu.se","@id":"https://orcid.org/0000-0003-2848-3326","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2021-09-14","datePublished":"2021-09-14","dateModified":"2021-09-14","keywords":"Radiology, Skull, CT, Computed tomography, Face blur, Male, Female","version":"1.0.0","description":"The data contains 300 skulls. The data is divided into three groups with 100\nscans in three categories Females, Males, and Mix. The purpose of the\nproject was to generate a machine learning algorithm to be able reconstruct\nmissing parts of the skull for cranioplasty. Each scan was verified to\nensure normal skull shape. To ensure data privacy the faces have\nbeen deblurred with an in-house developed algorithm.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/ctskull#controlled-access","@type":"CreativeWork","abstract":"Free for use in research or education.\n"},{"name":"AIDA license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/ctskull#aida-license","@type":"CreativeWork","abstract":"Free for use within AIDA."}],"citation":null},
    "other": {"shortName":"CTSKULL","origin":"Clinical","status":"Completed","annotation":"There are no annotations performed on the data set as segmentation of the\nskull shape is trivial by use of thresholding. All annotation in the\nproject was fully automated.\n","countries-shared":["CA","DE","IN","SE","US","SK"],"organ":[{"name":"Skull","sctid":89546000}],"age-span":"19-100","bytes":34427096021,"numberOfScans":300,"numberOfAnnotations":0,"resolution":"Typically 0.5 isotropic","modality":["CT"],"scanner":null,"stain":null,"phase":null,"image":null,"exampleImage":[{"title":"3D visualisation of typical coverage that goes down to the maxilla and covers the entire skull and including the mastoids.","url":"/assets/images/10.23698/aida/ctskull/sample-image.png","thumbnail-url":"/assets/images/10.23698/aida/ctskull/sample-image-thumbnail.png"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>Each study is zipped into one file. All files are stored in DICOM format.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in research or education.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the dataset reciever must be a teacher or at least a PhD candidate \nemployed at the applicant institution and that the applicant should be an \nauthorized signatory who can legally enter into data sharing agreements on \nthe behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/ctskull\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2021\nLund University, Einar Heiberg</p>\n\n<p>Permission to use, copy, modify, and/or distribute the data within AIDA\n(Analytic Imaging Diagnostics Arena https://medtech4health.se/aida) for the\npurpose of research or education with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Einar Heiberg and Finn Lennartsson\n(2021)\nCT of normal skulls in three categories (Female, Male, Mixed)\n<a href=\"https://doi.org/10.23698/aida/ctskull\">doi:10.23698/aida/ctskull</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/drbr","name":"Breast data from the Visual Sweden project DROID","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/drbr","author":[{"name":"Anna Bodén","@id":"https://orcid.org/0000-0002-0128-870X","@type":"Person"},{"name":"Jerónimo F. Rose","@id":"https://orcid.org/0000-0003-3845-8546","@type":"Person"},{"name":"Martin Lindvall","@id":"https://orcid.org/0000-0002-7014-8874","@type":"Person"},{"name":"Caroline Bivik Stadler","@id":"https://orcid.org/0000-0001-7250-234X","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Claes Lundström","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"provider":[{"name":"Claes Lundstrom","email":"claes.lundstrom@liu.se","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Anna Bodén","email":"Anna.C.Boden@regionostergotland.se","@id":"https://orcid.org/0000-0002-0128-870X","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2019-01-09","datePublished":"2019-01-09","dateModified":"2020-11-27","keywords":"Pathology, Breast, Cancer, Whole slide imaging, Annotated","version":"1.1.0","description":"This dataset consists of 361 whole slide images (WSI) - 296 malignant from\nwomen with invasive breast cancer (HER2 neg) and 65 benign. The tumours have\nbeen classified with four SNOMED-CT categories based on morphology: invasive\nduct carcinoma, invasive lobular carcinoma, in situ carcinoma, and others.\n4144 separate annotations have been made to segment different tissue\nstructures connected to ontologies.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drbr#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drbr#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"Article","@id":"https://doi.org/10.1007/s10278-020-00384-4","name":"Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n"}]},
    "other": {"shortName":"DRBR","origin":"Clinical","status":"Completed","annotation":"The breast tumours were classified with four SNOMED-CT categories based on\nmorphology: invasive duct carcinoma, Invasive lobular carcinoma, in situ\ncarcinoma and others. 4144 separate annotations were made to segment\ndifferent tissue structures connected to ontologies. One physician were\nresponsible for the manual annotations controlled by a second pathologist.\n","countries-shared":["AT","AU","CA","CN","DE","FI","FR","GB","NL","NO","PL","SE","US"],"organ":[{"name":"Breast","sctid":76752008}],"age-span":null,"bytes":500800073698,"numberOfScans":361,"numberOfAnnotations":4144,"resolution":"40X single plane, scanned in NDP format","modality":["SM"],"scanner":["Hamamatsu NanoZoomer-XR C12000 series 2013","Hamamatsu NanoZoomer 2.0 HT C9600 series 2013"],"stain":"H&E (hematoxylin and eosin)","phase":null,"exampleImage":[{"title":"Overview of whole slide imaging.","url":"/assets/images/10.23698/aida/drbr/wsi.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drbr/wsi-thumbnail.jpeg"},{"title":"Overview of annotations.","url":"/assets/images/10.23698/aida/drbr/annotations.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drbr/annotations-thumbnail.jpeg"},{"title":"Detail view of annotations.","url":"/assets/images/10.23698/aida/drbr/detail.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drbr/detail-thumbnail.jpeg"},{"title":"To-scale view of pixel resolution in original whole slide imaging data.","url":"/assets/images/10.23698/aida/drbr/to-scale.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drbr/to-scale-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<h3 id=\"pixel-position-scaling\">Pixel position scaling</h3>\n<p>Coordinates given are relative to the image <em>width</em>. To get the correct pixel\nposition, X coordinates (and Y coordinates!) should therefore be multiplied with\nthe image <em>width</em>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/drbr\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2019\nLinköping University, Claes Lundström</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Anna Bodén, Jerónimo F. Rose, Martin Lindvall, and Caroline Bivik Stadler\n(2019)\nBreast data from the Visual Sweden project DROID\n<a href=\"https://doi.org/10.23698/aida/drbr\">doi:10.23698/aida/drbr</a>.</p>\n\n<p><a href=\"https://doi.org/10.1007/s10278-020-00384-4\">Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/drco","name":"Colon data from the Visual Sweden project DROID","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/drco","author":[{"name":"Karin Lindman","@id":"https://orcid.org/0000-0003-1298-517X","@type":"Person"},{"name":"Martin Lindvall","@id":"https://orcid.org/0000-0002-7014-8874","@type":"Person"},{"name":"Caroline Bivik Stadler","@id":"https://orcid.org/0000-0001-7250-234X","@type":"Person"},{"name":"Claes Lundstrom","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Darren Treanor","@id":"https://orcid.org/0000-0002-4579-484X","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Claes Lundström","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"provider":[{"name":"Claes Lundstrom","email":"claes.lundstrom@liu.se","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Karin Lindman","email":"Karin.Lindman@regionostergotland.se","@id":"https://orcid.org/0000-0003-1298-517X","@type":"Person"},{"name":"Caroline Bivik Stadler","email":"caroline.bivik.stadler@liu.se","@id":"https://orcid.org/0000-0001-7250-234X","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2019-01-09","datePublished":"2019-01-09","dateModified":"2020-11-27","keywords":"Pathology, Colon, Cancer, Whole slide imaging, Annotated","version":"1.1.0","description":"The dataset consists of 101 H&E-stained colon whole slide images (WSI) - 52\nabnormal and 49 benign cases. All significant abnormal findings identified\nare outlined and categorized into 15 types such as hyperplastic polyp, high\ngrade adenocarcinoma and necrosis. Other tissue components such as mucosa,\nsubmucosa, as well as the surgical margin are delineated to create a\ncomplete histological map. In total, 756 separate annotations have been made\nto segment the different tissue structures and link them to ontological\ninformation.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drco#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drco#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"Article","@id":"https://doi.org/10.1007/s10278-020-00384-4","name":"Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n"}]},
    "other": {"shortName":"DRCO","origin":"Clinical","status":"Completed","annotation":"One physician was responsible for the manual annotations controlled by a\nsecond pathologist. Accurate annotations were made over the whole tissues.\n756 separate annotations were made.\n\nFollowing abnormal findings were annotated for the malign cases: acute and\nchronic inflammation, acute inflammation, adenocarcinoma, atrophy, chronic\ninflammation, diverticula, diverticulitis, dysplasia, edema, fibrosis,\ngranulations tissue, hemorrhage, hyalinization, hyperplasia, hyperplastic\npolyp, inflammation, lymphoma, mucinous adenocarcinoma, necrosis, serrated\nadenoma, stasis, tubular adenoma, tubulovillous adenoma and ulceration.\n\nOther areas annotated: abnormal, artifact, cecum, colon, colonic mucous\nmembrane, colonic muscularis propria, colonic submucosa, colonic subserosa,\ndescending colon, ileum, normal, rectum, sigmoid colon and transverse colon.\n\nFor the benign cases following areas were annotated: artifact, cecum, colon,\ncolonic mucous membrane, colonic muscularis propria, colonic submucosa,\ncolonic subserosa, descending colon, ileum, normal, rectum, sigmoid colon\nand transverse colon.\n","countries-shared":["AT","CH","CN","DE","FI","GB","NO","SE","US"],"organ":[{"name":"Colon","sctid":71854001}],"age-span":"22-90 years","bytes":49227373916,"numberOfScans":101,"numberOfAnnotations":756,"resolution":"20X and 40X single plane","modality":["SM"],"scanner":["Scanscope AT (Aperio, US)","NanoZoomer XR (Hamamatsu, Japan)","NanoZoomer XRL (Hamamatsu, Japan)"],"stain":"H&E (hematoxylin and eosin)","phase":null,"exampleImage":[{"title":"Overview of whole slide imaging.","url":"/assets/images/10.23698/aida/drco/wsi.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drco/wsi-thumbnail.jpeg"},{"title":"Overview of annotations.","url":"/assets/images/10.23698/aida/drco/annotations.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drco/annotations-thumbnail.jpeg"},{"title":"Overview of carcinoma whole slide imaging.","url":"/assets/images/10.23698/aida/drco/carcinoma.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drco/carcinoma-thumbnail.jpeg"},{"title":"Overview of carcinoma annotations.","url":"/assets/images/10.23698/aida/drco/carcinoma-annotations.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drco/carcinoma-annotations-thumbnail.jpeg"},{"title":"To-scale view of pixel resolution in original whole slide imaging data.","url":"/assets/images/10.23698/aida/drco/to-scale.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drco/to-scale-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<h3 id=\"pixel-position-scaling\">Pixel position scaling</h3>\n<p>Coordinates given are relative to the image <em>width</em>. To get the correct pixel\nposition, X coordinates (and Y coordinates!) should therefore be multiplied with\nthe image <em>width</em>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/drco\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2019\nLinköping University, Claes Lundström</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Karin Lindman, Martin Lindvall, Caroline Bivik Stadler, Claes Lundstrom, and Darren Treanor\n(2019)\nColon data from the Visual Sweden project DROID\n<a href=\"https://doi.org/10.23698/aida/drco\">doi:10.23698/aida/drco</a>.</p>\n\n<p><a href=\"https://doi.org/10.1007/s10278-020-00384-4\">Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/drli","name":"Liver data from the Visual Sweden project DROID","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/drli","author":[{"name":"Mischa Woisetschläger","@id":"https://orcid.org/0000-0003-0066-4985","@type":"Person"},{"name":"Johan Blomma","@type":"Person"},{"name":"Nils Dahlström","@id":"https://orcid.org/0000-0002-4111-1693","@type":"Person"},{"name":"Caroline Bivik Stadler","@id":"https://orcid.org/0000-0001-7250-234X","@type":"Person"},{"name":"Daniel Forsberg","@id":"https://orcid.org/0000-0003-0908-9470","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Anders Persson","@id":"https://orcid.org/0000-0002-9446-6981","@type":"Person"}],"provider":[{"name":"Mischa Woisetschläger","email":"Mischa.Woisetschlager@regionostergotland.se","@id":"https://orcid.org/0000-0003-0066-4985","@type":"Person"},{"name":"Anders Persson","email":"anders.s.persson@liu.se","@id":"https://orcid.org/0000-0002-9446-6981","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2019-01-09","datePublished":"2019-01-09","dateModified":"2020-11-27","keywords":"Radiology, Liver, Cancer, Computed tomography, Annotated","version":"1.1.0","description":"77 CT abdomen (computed tomography) examinations taken with contrast in\nvenous phase. All cases showed liver malignancies. Manual oncological\nannotations were made by a radiologist and these were controlled by a second\nexperienced radiologist. All changes with a diameter greater than 5mm were\nsegmented and assumed metastases (cysts excluded as defined by HU). 317\nlesions were annotated.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drli#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drli#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"Article","@id":"https://doi.org/10.1007/s10278-020-00384-4","name":"Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n"}]},
    "other": {"shortName":"DRLI","origin":"Clinical","status":"Completed","annotation":"Manual oncological annotations was made by a radiologist and these were\ncontrolled by a second radiologist. All changes with a diameter greater than\n5mm was segmented and as assumed metastases (cysts excluded defined by HU).\n317 lesions were annotated.\n","countries-shared":["GB","SE","US"],"organ":[{"name":"Liver","sctid":10200004}],"age-span":null,"bytes":33800000000,"numberOfScans":77,"numberOfAnnotations":317,"resolution":null,"modality":["CT"],"scanner":["Siemens CT Scanners"],"stain":null,"phase":"Venuous (with contrast)","exampleImage":[{"title":"3D illustration of locations, sizes and distribution in liver metastasis (green).","url":"/assets/images/10.23698/aida/drli/3d.png","thumbnail-url":"/assets/images/10.23698/aida/drli/3d-thumbnail.png"},{"title":"Slice from thorax CT stack with annotated liver metastases.","url":"/assets/images/10.23698/aida/drli/slice.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drli/slice-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>DICOM. Please see our help pages for some examples of\n<a href=\"https://docs.datahub.aida.scilifelab.se/data/working-with-dicom/\">working with DICOM</a>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.\nPlease contact the dataset provider for terms of access.</p>\n\n<p>You are invited to send an\n<a href=\"mailto:Mischa.Woisetschlager@regionostergotland.se?cc=anders.s.persson@liu.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/drli&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fdrli%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fdrli%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">access request email</a>\nfrom your institutional account.</p>\n\n<p>Clicking the access request email link above should open a draft email message\nin a new window, to help you provide relevant information for efficient request\nevaluation. If the above link does not work for you, then please click to view the\n<a id=\"request-email-toggle\">suggested email text</a>.</p>\n\n<div id=\"request-email\" class=\"hidden revealable small\">\n<b>To</b>: Mischa.Woisetschlager@regionostergotland.se<br />\n<b>cc</b>: anders.s.persson@liu.se,aida-data@nbis.se<br />  \n<b>Subject</b>: Requesting access to dataset doi:10.23698/aida/drli<br />\nHi!<br />\n<br />\nI work at INSTITUTION in COUNTRY, emailing from my institutional account.<br />\n<br />\nI would like to access the dataset doi:10.23698/aida/drli, for use in ethical and legal medical diagnostics research. Could you please send me a data sharing agreement template?<br />\n<br />\nOur planned use of the data can be summarized as:<br />\n<br />\nBRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES<br />\n<br />\nDataset: https://datahub.aida.scilifelab.se/10.23698/aida/drli<br />\n<br />\nExample agreement template: https://datahub.aida.scilifelab.se/sharing/templates/<br />\n<br />\nTemplate placeholders:<br />\n<br />\nResearch PI (\"Recipient Scientist\"):<br />\nName: PI_NAME (cc here)<br />\nTitle: PI_TITLE (ph d or better, in relevant field)<br />\n<br />\nName of institution: INSTITUTION_NAME<br />\nName of department: DEPARTMENT_NAME<br />\nInstitution postal address: POSTAL_ADDRESS<br />\n<br />\nAuthorized signatory (if other than research PI):<br />\nName: SIGNATORY_NAME (cc here)<br />\nTitle: SIGNATORY_TITLE<br />\n<br />\nThe Research PI has a PhD degree or better in a relevant field, and their institutional email address is in CC in this email conversation. The Authorized signatory is the person who signs this type of legal agreement on behalf of this institution, and their institutional email address is in CC in this conversation.<br />\n<br />\n/MY_NAME<br />\n<br />\nClick to <a href=\"mailto:Mischa.Woisetschlager@regionostergotland.se?cc=anders.s.persson@liu.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/drli&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fdrli%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fdrli%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">create draft email</a> (new window). Use your institutional account.\n</div>\n<script>\ndocument.querySelector(\"#request-email-toggle\").addEventListener('click', (e) => {\n  document.querySelector(\"#request-email\").classList.toggle('hidden')\n  })\n</script>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2019\nLinköping University, Anders Persson</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Mischa Woisetschläger, Johan Blomma, Nils Dahlström, Caroline Bivik Stadler, and Daniel Forsberg\n(2019)\nLiver data from the Visual Sweden project DROID\n<a href=\"https://doi.org/10.23698/aida/drli\">doi:10.23698/aida/drli</a>.</p>\n\n<p><a href=\"https://doi.org/10.1007/s10278-020-00384-4\">Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/drov","name":"Ovary data from the Visual Sweden project DROID","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/drov","author":[{"name":"Karin Lindman","@id":"https://orcid.org/0000-0003-1298-517X","@type":"Person"},{"name":"Jerónimo F. Rose","@id":"https://orcid.org/0000-0003-3845-8546","@type":"Person"},{"name":"Martin Lindvall","@id":"https://orcid.org/0000-0002-7014-8874","@type":"Person"},{"name":"Caroline Bivik Stadler","@id":"https://orcid.org/0000-0001-7250-234X","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Claes Lundström","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"provider":[{"name":"Claes Lundstrom","email":"claes.lundstrom@liu.se","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Karin Lindman","email":"Karin.Lindman@regionostergotland.se","@id":"https://orcid.org/0000-0003-1298-517X","@type":"Person"},{"name":"Caroline Bivik Stadler","email":"caroline.bivik.stadler@liu.se","@id":"https://orcid.org/0000-0001-7250-234X","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2019-01-09","datePublished":"2019-01-09","dateModified":"2020-11-27","keywords":"Pathology, Ovary, Cancer, Whole slide imaging, Annotated","version":"1.1.0","description":"This dataset consists of 174 WSI ovary whole slide images (WSI): 158\nmalignant and 16 benign. Eight of the most common, histological definable\ntumour types were annotated: high grade serous carcinoma (HGSC), low grade\nserous carcinoma (LGSC), clear cell carcinoma (CC), endometrioid\nadenocarcinoma (EN), metastastic serous carcinoma (MS), metastatic other\n(MO), serous borderline tumor (SB) and mucinous borderline tumor (MB). Also\nnormal ovarian tissue were annotated. 2402 separate annotations were made.\nFor the benign structures only the epithelial structures, stroma and support\ntissue were annotated.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drov#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drov#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"Article","@id":"https://doi.org/10.1007/s10278-020-00384-4","name":"Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n"}]},
    "other": {"shortName":"DROV","origin":"Clinical","status":"Completed","annotation":"One physician was responsible for the manual annotations controlled by a second\npathologist.\n\nEight of the most common, histological definable tumour types were\nannotated: high grade serous carcinoma (HGSC), low grade serous carcinoma\n(LGSC), clear cell carcinoma (CC), endometrioid adenocarcinoma (EN),\nmetastastic serous carcinoma (MS), metastatic other (MO), serous borderline\ntumor (SB) and mucinous borderline tumor (MB). Also normal ovarian tissue\nwas annotated. In total 2402 separate annotations were made. For the\nbenign structures only the epithelial structures, stroma and support tissue\nwere annotated.\n","countries-shared":["AT","BD","CN","DE","FR","GB","SE","US"],"organ":[{"name":"Ovary","sctid":15497006}],"age-span":"17-86 years","bytes":108588106975,"numberOfScans":193,"numberOfAnnotations":2402,"resolution":"20X single plane","modality":["SM"],"scanner":["Scanscope AT (Aperio, US)","NanoZoomer XR (Hamamatsu, Japan)","NanoZoomer XRL (Hamamatsu, Japan)"],"stain":"H&E (hematoxylin and eosin)","phase":null,"exampleImage":[{"title":"Overview of whole slide imaging.","url":"/assets/images/10.23698/aida/drov/wsi.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drov/wsi-thumbnail.jpeg"},{"title":"Overview of annotations.","url":"/assets/images/10.23698/aida/drov/annotations.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drov/annotations-thumbnail.jpeg"},{"title":"Detail view of annotations.","url":"/assets/images/10.23698/aida/drov/detail.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drov/detail-thumbnail.jpeg"},{"title":"To-scale view of pixel resolution in original whole slide imaging data.","url":"/assets/images/10.23698/aida/drov/to-scale.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drov/to-scale-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<h3 id=\"pixel-position-scaling\">Pixel position scaling</h3>\n<p>Coordinates given are relative to the image <em>width</em>. To get the correct pixel\nposition, X coordinates (and Y coordinates!) should therefore be multiplied with\nthe image <em>width</em>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/drov\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2019\nLinköping University, Claes Lundström</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Karin Lindman, Jerónimo F. Rose, Martin Lindvall, and Caroline Bivik Stadler\n(2019)\nOvary data from the Visual Sweden project DROID\n<a href=\"https://doi.org/10.23698/aida/drov\">doi:10.23698/aida/drov</a>.</p>\n\n<p><a href=\"https://doi.org/10.1007/s10278-020-00384-4\">Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/drsk","name":"Skin data from the Visual Sweden project DROID","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/drsk","author":[{"name":"Karin Lindman","@id":"https://orcid.org/0000-0003-1298-517X","@type":"Person"},{"name":"Jerónimo F. Rose","@id":"https://orcid.org/0000-0003-3845-8546","@type":"Person"},{"name":"Martin Lindvall","@id":"https://orcid.org/0000-0002-7014-8874","@type":"Person"},{"name":"Caroline Bivik Stadler","@id":"https://orcid.org/0000-0001-7250-234X","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Claes Lundström","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"provider":[{"name":"Claes Lundstrom","email":"claes.lundstrom@liu.se","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Karin Lindman","email":"Karin.Lindman@regionostergotland.se","@id":"https://orcid.org/0000-0003-1298-517X","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2019-01-09","datePublished":"2019-01-09","dateModified":"2020-11-27","keywords":"Pathology, Skin, Cancer, Whole slide imaging, Annotated","version":"1.1.0","description":"The dataset consists of 99 H&E-stained whole slide skin images (WSI) - 49\nabnormal and 50 normal cases. All significant abnormal findings identified\nare outlined and categorized into 13 types such as actinic keratosis, basal\ncell carcinoma and dermatofibroma. Other tissue components, such as\nepidermis, adnexal structures, as well as the surgical margin are delineated\nto create a complete histological map. In total, 16741 separate annotations\nhave been made to segment the different tissue structures and link them to\nontological information.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drsk#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drsk#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"Article","@id":"https://doi.org/10.1007/s10278-020-00384-4","name":"Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n"}]},
    "other": {"shortName":"DRSK","origin":"Clinical","status":"Completed","annotation":"One physician was responsible for the manual annotations controlled by a\nsecond pathologist. Accurate annotations were made over the whole tissues.\n16741 separate annotations were made.\n\nThe following findings were annotated in the abnormal cases: actinic\nkeratosis, basal cell carcinoma, dermatofibroma, dysplastic nevus,\nintradermal nevus, keratoachantoma, lentigo malignant melanoma, malignant\nmelanoma, malignant melanoma in situ, scar, seborrheic keratosis, squamous\ncell carcinoma and squamous cell carcinoma in situ. Other areas annotated:\nabnormal, acanthosis, artifacts, dermis, epidermis, fibrosis, fibrin body,\ngranuloma, inflammation, inflammatory edema, normal, perichondrium, reactive\ncellular changes, skin appendage structure, surgical margins, structure of\ncartilage of auditory canal, subcutaneous fatty tissue, subcutaneous tissue,\nsurgical margins and from which body part the skin was excised.\n\nIn the normal skin cases were following structures chosen to be annotated:\nartifact, dermis, epidermis, normal skin, perichondrium, skin and\nsubcutaneous structure, skin appendage structure, skin structure, structure\nof cartilage of auditory canal, subcutaneous fatty tissue, subcutaneous\ntissue and surgical margins.\n","countries-shared":["AT","CN","DE","ES","FI","FR","GB","IT","NL","NO","SE","US"],"organ":[{"name":"Skin","sctid":39937001}],"age-span":"20-93 years","bytes":32362326070,"numberOfScans":99,"numberOfAnnotations":16741,"resolution":"20X single plane","modality":["SM"],"scanner":["Scanscope AT (Aperio, US)","NanoZoomer XR (Hamamatsu, Japan)","NanoZoomer XRL (Hamamatsu, Japan)"],"stain":"H&E (hematoxylin and eosin)","phase":null,"exampleImage":[{"title":"Overview of whole slide imaging.","url":"/assets/images/10.23698/aida/drsk/wsi.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drsk/wsi-thumbnail.jpeg"},{"title":"Overview of annotations.","url":"/assets/images/10.23698/aida/drsk/wsi-annotations.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drsk/wsi-annotations-thumbnail.jpeg"},{"title":"Detail view of abnormal findings.","url":"/assets/images/10.23698/aida/drsk/detail.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drsk/detail-thumbnail.jpeg"},{"title":"Detail view of annotations.","url":"/assets/images/10.23698/aida/drsk/detail-annotations.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drsk/detail-annotations-thumbnail.jpeg"},{"title":"To-scale view of pixel resolution in original whole slide imaging data.","url":"/assets/images/10.23698/aida/drsk/to-scale.jpeg","thumbnail-url":"/assets/images/10.23698/aida/drsk/to-scale-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<h3 id=\"pixel-position-scaling\">Pixel position scaling</h3>\n<p>Coordinates given are relative to the image <em>width</em>. To get the correct pixel\nposition, X coordinates (and Y coordinates!) should therefore be multiplied with\nthe image <em>width</em>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/drsk\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2019\nLinköping University, Claes Lundström</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Karin Lindman, Jerónimo F. Rose, Martin Lindvall, and Caroline Bivik Stadler\n(2019)\nSkin data from the Visual Sweden project DROID\n<a href=\"https://doi.org/10.23698/aida/drsk\">doi:</a>.</p>\n\n<p><a href=\"https://doi.org/10.1007/s10278-020-00384-4\">Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/drske","name":"Skeletal data from the Visual Sweden project DROID","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/drske","author":[{"name":"Mischa Woisetschläger","@id":"https://orcid.org/0000-0003-0066-4985","@type":"Person"},{"name":"Filip Landgren","@type":"Person"},{"name":"Caroline Bivik Stadler","@id":"https://orcid.org/0000-0001-7250-234X","@type":"Person"},{"name":"Daniel Forsberg","@id":"https://orcid.org/0000-0003-0908-9470\t","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Anders Persson","@id":"https://orcid.org/0000-0002-9446-6981","@type":"Person"}],"provider":[{"name":"Mischa Woisetschläger","email":"Mischa.Woisetschlager@regionostergotland.se","@type":"Person","@id":"https://orcid.org/0000-0003-0066-4985"},{"name":"Anders Persson","email":"anders.s.persson@liu.se","@id":"https://orcid.org/0000-0002-9446-6981","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2019-01-09","datePublished":"2019-01-09","dateModified":"2020-11-27","keywords":"Radiology, Bone, Cancer, Metastasis, Computed tomography, Annotated","version":"1.1.0","description":"36 radiology cases showing lytic and lytic/sclerotic (blastic) metastases\ni.e. bone regenerative and degenerative. These cases have all been punctured\nand pathologically analyzed to verify the diagnose. The metastases were\nsegmented accurately by a radiologist and the annotations were confirmed by\na second radiologist.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drske#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/drske#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"Article","@id":"https://doi.org/10.1007/s10278-020-00384-4","name":"Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n"}]},
    "other": {"shortName":"DRSKE","origin":"Clinical","status":"Completed","annotation":"The metastases were segmented accurately by a radiologist and the\nannotations were confirmed by a second radiologist.\n","countries-shared":["SE","US"],"organ":[{"name":"Skeleton","sctid":113192009}],"age-span":null,"bytes":14900000000,"numberOfScans":36,"numberOfAnnotations":null,"resolution":null,"modality":["CT"],"scanner":null,"stain":null,"phase":null,"exampleImage":[{"title":"A 3D visualization of the region. The crosshair indicates the location of the lytic metastasis.","url":"/assets/images/10.23698/aida/drske/3d.png","thumbnail-url":"/assets/images/10.23698/aida/drske/3d-thumbnail.png"},{"title":"Slice from thorax CT stack with annotated sclerotic and lytic bone metastases.","url":"/assets/images/10.23698/aida/drske/slice.png","thumbnail-url":"/assets/images/10.23698/aida/drske/slice-thumbnail.png"},{"title":"Annotation of sclerotic metastasis.","url":"/assets/images/10.23698/aida/drske/sclerotic.png","thumbnail-url":"/assets/images/10.23698/aida/drske/sclerotic-thumbnail.png"},{"title":"Annotation of lytic metastasis.","url":"/assets/images/10.23698/aida/drske/lytic.png","thumbnail-url":"/assets/images/10.23698/aida/drske/lytic-thumbnail.png"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>DICOM. Please see our help pages for some examples of\n<a href=\"https://docs.datahub.aida.scilifelab.se/data/working-with-dicom/\">working with DICOM</a>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.\nPlease contact the dataset provider for terms of access.</p>\n\n<p>You are invited to send an\n<a href=\"mailto:Mischa.Woisetschlager@regionostergotland.se?cc=anders.s.persson@liu.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/drske&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fdrske%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fdrske%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">access request email</a>\nfrom your institutional account.</p>\n\n<p>Clicking the access request email link above should open a draft email message\nin a new window, to help you provide relevant information for efficient request\nevaluation. If the above link does not work for you, then please click to view the\n<a id=\"request-email-toggle\">suggested email text</a>.</p>\n\n<div id=\"request-email\" class=\"hidden revealable small\">\n<b>To</b>: Mischa.Woisetschlager@regionostergotland.se<br />\n<b>cc</b>: anders.s.persson@liu.se,aida-data@nbis.se<br />  \n<b>Subject</b>: Requesting access to dataset doi:10.23698/aida/drske<br />\nHi!<br />\n<br />\nI work at INSTITUTION in COUNTRY, emailing from my institutional account.<br />\n<br />\nI would like to access the dataset doi:10.23698/aida/drske, for use in ethical and legal medical diagnostics research. Could you please send me a data sharing agreement template?<br />\n<br />\nOur planned use of the data can be summarized as:<br />\n<br />\nBRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES<br />\n<br />\nDataset: https://datahub.aida.scilifelab.se/10.23698/aida/drske<br />\n<br />\nExample agreement template: https://datahub.aida.scilifelab.se/sharing/templates/<br />\n<br />\nTemplate placeholders:<br />\n<br />\nResearch PI (\"Recipient Scientist\"):<br />\nName: PI_NAME (cc here)<br />\nTitle: PI_TITLE (ph d or better, in relevant field)<br />\n<br />\nName of institution: INSTITUTION_NAME<br />\nName of department: DEPARTMENT_NAME<br />\nInstitution postal address: POSTAL_ADDRESS<br />\n<br />\nAuthorized signatory (if other than research PI):<br />\nName: SIGNATORY_NAME (cc here)<br />\nTitle: SIGNATORY_TITLE<br />\n<br />\nThe Research PI has a PhD degree or better in a relevant field, and their institutional email address is in CC in this email conversation. The Authorized signatory is the person who signs this type of legal agreement on behalf of this institution, and their institutional email address is in CC in this conversation.<br />\n<br />\n/MY_NAME<br />\n<br />\nClick to <a href=\"mailto:Mischa.Woisetschlager@regionostergotland.se?cc=anders.s.persson@liu.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/drske&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fdrske%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fdrske%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">create draft email</a> (new window). Use your institutional account.\n</div>\n<script>\ndocument.querySelector(\"#request-email-toggle\").addEventListener('click', (e) => {\n  document.querySelector(\"#request-email\").classList.toggle('hidden')\n  })\n</script>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2019\nLinköping University, Anders Persson</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Mischa Woisetschläger, Filip Landgren, Caroline Bivik Stadler, and Daniel Forsberg\n(2019)\nSkeletal data from the Visual Sweden project DROID\n<a href=\"https://doi.org/10.23698/aida/drske\">doi:10.23698/aida/drske</a>.</p>\n\n<p><a href=\"https://doi.org/10.1007/s10278-020-00384-4\">Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction\nof an Annotated Imaging Database for Artificial Intelligence Training.\nJ Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4\n</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/ejr2023","name":"Elbow radiographs with classified fractures according to 2018 AO/OTA and classified degenerative conditions","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/ejr2023","author":[{"name":"Annelie Pettersson","@type":"Person"},{"name":"Teo Stukan","@id":"https://orcid.org/0000-0002-4855-5115","@type":"Person"},{"name":"Oscar Ljungberg","@type":"Person"},{"name":"Hans Nåsell","@type":"Person"},{"name":"Ali Sharif Razavian","@type":"Person"},{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2023,"copyrightHolder":[{"name":"Karolinska Institutet","url":"https://ki.se/","@type":"Organization"},{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"provider":[{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"},{"name":"Max Gordon","email":"max.gordon@ki.se","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"},{"name":"Martin Magnéli","email":"martin.magneli@ki.se","@id":"https://orcid.org/0000-0003-0341-0227","@type":"Person"}],"dateCreated":"2023-06-14","datePublished":"2023-06-15","dateModified":"2023-06-15","keywords":"Radiology, Plain radiographs, Elbow, Humerus, Ulna, Radius, Fracture, Osteoarthritis, Effusion, Implants, AO/OTA","version":"1.0.0","description":"A dataset containing 739 elbow radiographs from 201 patients. Fractures in the humeroulnar, humeroradial, and proximal radioulnar joints are classified according to the 2018 AO/OTA classification system. The radiographs are also classified for degenerative conditions such as osteoarthritis, effusion, implants, and dislocation. The radiographs are classified by experienced orthopaedic surgeons.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/ejr2023#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/ejr2023#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":null},
    "other": {"shortName":"EJR2023","origin":"Clinical","status":"Ongoing","annotation":"Manually annotated by experienced orthopedic surgeons.\nDouble review of radiographs was performed, and the second review is always done by a specialized physician or someone with higher expertise. \nClassification for fractures according to 2018 AO/OTA\n","countries-shared":["SE"],"organ":[{"name":"Elbow","sctid":127949000}],"age-span":"16 and above","bytes":1420992468,"numberOfScans":739,"numberOfAnnotations":0,"resolution":"Various. Image sizes vary from 1499x1500 to 1500x413.","modality":["CR"],"scanner":null,"stain":null,"phase":null,"image":"/assets/images/10.23698/aida/ejr2023/1-lateral-olecranon-fracture-thumbnail.jpg","exampleImage":[{"title":"Lateral view of an olecranon fracture (2U1B1).","url":"/assets/images/10.23698/aida/ejr2023/1-lateral-olecranon-fracture.jpg","thumbnail-url":"/assets/images/10.23698/aida/ejr2023/1-lateral-olecranon-fracture-thumbnail.jpg"},{"title":"Lateral view of a proximal radius fracture (2R1A).","url":"/assets/images/10.23698/aida/ejr2023/2-lateral-proximal-radius-fracture.jpg","thumbnail-url":"/assets/images/10.23698/aida/ejr2023/2-lateral-proximal-radius-fracture-thumbnail.jpg"},{"title":"Frontal view of a proximal radius fracture (2R1B1).","url":"/assets/images/10.23698/aida/ejr2023/3-frontal-proximal-radius-fracture.jpg","thumbnail-url":"/assets/images/10.23698/aida/ejr2023/3-frontal-proximal-radius-fracture-thumbnail.jpg"},{"title":"Lateral view of a dislocated elbow joint.","url":"/assets/images/10.23698/aida/ejr2023/4-lateral-dislocated-elbow-joint.jpg","thumbnail-url":"/assets/images/10.23698/aida/ejr2023/4-lateral-dislocated-elbow-joint-thumbnail.jpg"},{"title":"Frontal view of a transverse distal humerus fracture (13A2.3).","url":"/assets/images/10.23698/aida/ejr2023/5-frontal-transverse-distal-humerus-fracture.jpg","thumbnail-url":"/assets/images/10.23698/aida/ejr2023/5-frontal-transverse-distal-humerus-fracture-thumbnail2.jpg"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.\nPlease contact AIDA for terms of access.</p>\n\n<p>You are invited to send an\n<a href=\"mailto:aida-data@nbis.se?cc=max.gordon@ki.se,martin.magneli@ki.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/ejr2023&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fejr2023%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fejr2023%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">access request email</a>\nfrom your institutional account.</p>\n\n<p>Clicking the access request email link above should open a draft email message\nin a new window, to help you provide relevant information for efficient request\nevaluation. If the above link does not work for you, then please click to view the\n<a id=\"request-email-toggle\">suggested email text</a>.</p>\n\n<div id=\"request-email\" class=\"hidden revealable small\">\n<b>To</b>: aida-data@nbis.se<br />\n<b>cc</b>: max.gordon@ki.se,martin.magneli@ki.se<br />  \n<b>Subject</b>: Requesting access to dataset doi:10.23698/aida/ejr2023<br />\nHi!<br />\n<br />\nI work at INSTITUTION in COUNTRY, emailing from my institutional account.<br />\n<br />\nI would like to access the dataset doi:10.23698/aida/ejr2023, for use in ethical and legal medical diagnostics research. Could you please send me a data sharing agreement template?<br />\n<br />\nOur planned use of the data can be summarized as:<br />\n<br />\nBRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES<br />\n<br />\nDataset: https://datahub.aida.scilifelab.se/10.23698/aida/ejr2023<br />\n<br />\nExample agreement template: https://datahub.aida.scilifelab.se/sharing/templates/<br />\n<br />\nTemplate placeholders:<br />\n<br />\nResearch PI (\"Recipient Scientist\"):<br />\nName: PI_NAME (cc here)<br />\nTitle: PI_TITLE (ph d or better, in relevant field)<br />\n<br />\nName of institution: INSTITUTION_NAME<br />\nName of department: DEPARTMENT_NAME<br />\nInstitution postal address: POSTAL_ADDRESS<br />\n<br />\nAuthorized signatory (if other than research PI):<br />\nName: SIGNATORY_NAME (cc here)<br />\nTitle: SIGNATORY_TITLE<br />\n<br />\nThe Research PI has a PhD degree or better in a relevant field, and their institutional email address is in CC in this email conversation. The Authorized signatory is the person who signs this type of legal agreement on behalf of this institution, and their institutional email address is in CC in this conversation.<br />\n<br />\n/MY_NAME<br />\n<br />\nClick to <a href=\"mailto:aida-data@nbis.se?cc=max.gordon@ki.se,martin.magneli@ki.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/ejr2023&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fejr2023%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fejr2023%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">create draft email</a> (new window). Use your institutional account.\n</div>\n<script>\ndocument.querySelector(\"#request-email-toggle\").addEventListener('click', (e) => {\n  document.querySelector(\"#request-email\").classList.toggle('hidden')\n  })\n</script>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2023\nKarolinska Institutet, Max Gordon</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Annelie Pettersson, Teo Stukan, Oscar Ljungberg, Hans Nåsell, Ali Sharif Razavian, and Max Gordon\n(2023)\nElbow radiographs with classified fractures according to 2018 AO/OTA and classified degenerative conditions\n<a href=\"https://doi.org/10.23698/aida/ejr2023\">doi:10.23698/aida/ejr2023</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/kf2020","name":"Knee fracture classification according to AO/OTA 2018","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/kf2020","author":[{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"},{"name":"Olof Sköldenberg","@id":"https://orcid.org/0000-0003-4155-8425","@type":"Person"},{"name":"Ehsan Akbarian","@id":"https://orcid.org/0000-0002-6496-578X","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2021,"copyrightHolder":[{"name":"Karolinska Institutet","url":"https://ki.se/","@type":"Organization"},{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"provider":[{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"},{"name":"Max Gordon","email":"max.gordon@ki.se","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"dateCreated":"2021-02-02","datePublished":"2021-03-10","dateModified":"2021-03-10","keywords":"Radiology, Computed radiography, Knee, Radiographs, Fractures, AO-classification","version":"1.0.1","description":"Test set used for knee fracture classification using the AO/OTA 2018 classification.\n2472 images from 600 examinations. OpenAccess article available [here](https://doi.org/10.1371/journal.pone.0248809).\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/kf2020#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/kf2020#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.1371/journal.pone.0248809","name":"Lind A, Akbarian E, Olsson S, Nåsell H, Sköldenberg O, Razavian AS, et al. (2021) Artificial intelligence for the classification of fractures around the knee in adults according to the 2018 AO/OTA classification system. PLoS ONE 16(4): e0248809. https://doi.org/10.1371/journal.pone.0248809"}]},
    "other": {"shortName":"KF2020","origin":"Clinical","status":"Completed","annotation":"Manually annotated by experienced orthopedic surgeons.\n","countries-shared":["CL","ES","IN","SE","TW","US","ZA"],"organ":[{"name":"Knee","sctid":72696002}],"age-span":"15+","bytes":3067959667,"numberOfScans":2472,"numberOfAnnotations":null,"resolution":"Various. Image sizes vary from 800x600px to 2000x1000px.","modality":["CR"],"scanner":null,"stain":null,"phase":null,"image":"/assets/images/10.23698/aida/kf2020/frontal-knee-thumbnail.png","exampleImage":[{"title":"Frontal knee radiograph.","url":"/assets/images/10.23698/aida/kf2020/frontal-knee.png","thumbnail-url":"/assets/images/10.23698/aida/kf2020/frontal-knee-thumbnail.png"},{"title":"Patella view.","url":"/assets/images/10.23698/aida/kf2020/patella-view.png","thumbnail-url":"/assets/images/10.23698/aida/kf2020/patella-view-thumbnail.png"},{"title":"Lateral view with TKA.","url":"/assets/images/10.23698/aida/kf2020/lateral-view-with-tka.png","thumbnail-url":"/assets/images/10.23698/aida/kf2020/lateral-view-with-tka-thumbnail.png"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/kf2020\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2021\nKarolinska Institutet, Max Gordon</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Max Gordon, Olof Sköldenberg, and Ehsan Akbarian\n(2021)\nKnee fracture classification according to AO/OTA 2018\n<a href=\"https://doi.org/10.23698/aida/kf2020\">doi:10.23698/aida/kf2020</a>.</p>\n\n<p><a href=\"https://doi.org/10.1371/journal.pone.0248809\">Lind A, Akbarian E, Olsson S, Nåsell H, Sköldenberg O, Razavian AS, et al. (2021) Artificial intelligence for the classification of fractures around the knee in adults according to the 2018 AO/OTA classification system. PLoS ONE 16(4): e0248809. https://doi.org/10.1371/journal.pone.0248809</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/koa2021","name":"Knee osteoarthritis classification according to Kellgren-Lawrence","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/koa2021","author":[{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"},{"name":"Ehsan Akbarian","@id":"https://orcid.org/0000-0002-6496-578X","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2021,"copyrightHolder":[{"name":"Karolinska Institutet","url":"https://ki.se/","@type":"Organization"},{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"provider":[{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"},{"name":"Max Gordon","email":"max.gordon@ki.se","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"dateCreated":"2021-08-24","datePublished":"2021-08-24","dateModified":"2021-08-24","keywords":"Radiology, Computed radiography, Knee, Radiographs, Osteoarthritis","version":"1.0.0","description":"Test set used for knee osteoarthritis classification according to the\nKellgren-Lawrence classification. 1121 images from 300 exams. OpenAccess\narticle available [here](https://doi.org/10.1186/s12891-021-04722-7).\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/koa2021#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/koa2021#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.1186/s12891-021-04722-7","name":"Olsson, S., Akbarian, E., Lind, A. et al. Automating classification of osteoarthritis according to Kellgren-Lawrence in the knee using deep learning in an unfiltered adult population. BMC Musculoskelet Disord 22, 844 (2021). https://doi.org/10.1186/s12891-021-04722-7"}]},
    "other": {"shortName":"KOA2021","origin":"Clinical","status":"Completed","annotation":"Manually annotated by experienced orthopedic surgeons with a consensus\nsession for exams with disagreement in any of the classes.\n","countries-shared":["BD","CN","ES","IN","IR","PK","SE","US"],"organ":[{"name":"Knee","sctid":72696002}],"age-span":"15+","bytes":1396829896,"numberOfScans":1121,"numberOfAnnotations":null,"resolution":null,"modality":["CR"],"scanner":null,"stain":null,"phase":null,"image":"/assets/images/10.23698/aida/koa2021/frontal-knee-2-thumbnail.png","exampleImage":[{"title":"Frontal knee.","url":"/assets/images/10.23698/aida/koa2021/frontal-knee-1.png","thumbnail-url":"/assets/images/10.23698/aida/koa2021/frontal-knee-1-thumbnail.png"},{"title":"HKA-measurement.","url":"/assets/images/10.23698/aida/koa2021/hka-measurement.png","thumbnail-url":"/assets/images/10.23698/aida/koa2021/hka-measurement-thumbnail.png"},{"title":"Frontal knee.","url":"/assets/images/10.23698/aida/koa2021/frontal-knee-2.png","thumbnail-url":"/assets/images/10.23698/aida/koa2021/frontal-knee-2-thumbnail.png"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/koa2021\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2021\nKarolinska Institutet, Max Gordon</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Max Gordon and Ehsan Akbarian\n(2021)\nKnee osteoarthritis classification according to Kellgren-Lawrence\n<a href=\"https://doi.org/10.23698/aida/koa2021\">doi:10.23698/aida/koa2021</a>.</p>\n\n<p><a href=\"https://doi.org/10.1186/s12891-021-04722-7\">Olsson, S., Akbarian, E., Lind, A. et al. Automating classification of osteoarthritis according to Kellgren-Lawrence in the knee using deep learning in an unfiltered adult population. BMC Musculoskelet Disord 22, 844 (2021). https://doi.org/10.1186/s12891-021-04722-7</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/lesser","name":"Low-resolution prostate MR","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/lesser","author":[{"name":"Samuel Fransson","@id":"https://orcid.org/0000-0002-7883-5724","@type":"Person"},{"name":"Robin Strand","@id":"https://orcid.org/0000-0001-7764-1787","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2022,"copyrightHolder":[{"name":"Medical Physics Region Uppsala","url":"https://www.akademiska.se/","@type":"Organization"},{"name":"Alexander Englund","@type":"Person"},{"name":"Uppsala University","url":"https://www.uu.se/","@type":"Organization"},{"name":"Robin Strand","@id":"https://orcid.org/0000-0001-7764-1787","@type":"Person"}],"provider":[{"name":"Samuel Fransson","email":"samuel.fransson@akademiska.se","@id":"https://orcid.org/0000-0002-7883-5724","@type":"Person"},{"name":"Robin Strand","email":"robin.strand@it.uu.se","@id":"https://orcid.org/0000-0001-7764-1787","@type":"Person"},{"name":"Alexander Englund","email":"alexander.englund@akademiska.se","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2022-12-09","datePublished":"2023-11-01","dateModified":"2023-11-01","keywords":"Radiology, Annotated, MR-Linac, Radiotherapy, Prostate, Low-resolution","version":"1.0","description":"MR-images of the prostate region from healthy volunteers acquired at Elekta unity MR-Linac at Uppsala University Hospital. Data from each volunteer consist of an initial T2-weighted scan, followed by a number of groups of paired low and high resolution data approximately 5 minutes apart with a 3D balanced steady state free precession sequence. The initial T2-image and all high resolution images are segmented by a single observer including prostate, bladder and rectum.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/lesser#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/lesser#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"Article","@id":"https://doi.org/10.1080/17453674.2021.1891512","name":"Samuel Fransson, David Tilly, and Robin Strand (2023) Deep learning segmentation of low-resolution images for prostate magnetic resonance-guided radiotherapy, DOI: 10.48550/arXiv.2310.11358\n"}]},
    "other": {"shortName":"LESSER","origin":"Clinical","status":"Completed","annotation":"All initial T2-weighted scans along with the high resolution images in each paired low and high resolution group are segmented by a single observer in Monaco 5.40.01 and containing delineations of prostate (CTV), bladder and rectum.\n","countries-shared":["CN","SE"],"organ":[{"name":"Prostate","sctid":41216001}],"age-span":null,"bytes":5690831667,"numberOfScans":310,"numberOfAnnotations":255,"resolution":"Varying","modality":["MR"],"scanner":["Marlin 1.5 T, Elekta Unity"],"stain":null,"phase":null,"exampleImage":[{"title":"Example transversal images of different resolution levels and delineations.","url":"/assets/images/10.23698/aida/lesser/LESSER_1_transversal.png","thumbnail-url":"/assets/images/10.23698/aida/lesser/LESSER_1_transversal-thumbnail.png"},{"title":"Example sagittal images of different resolution levels and delineations.","url":"/assets/images/10.23698/aida/lesser/LESSER_2_sagittal.png","thumbnail-url":"/assets/images/10.23698/aida/lesser/LESSER_2_sagittal-thumbnail.png"},{"title":"Example coronal images of different resolution levels and delineations.","url":"/assets/images/10.23698/aida/lesser/LESSER_3_coronal.png","thumbnail-url":"/assets/images/10.23698/aida/lesser/LESSER_3_coronal-thumbnail.png"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.\nPlease contact the dataset provider for terms of access.</p>\n\n<p>You are invited to send an\n<a href=\"mailto:samuel.fransson@akademiska.se?cc=robin.strand@it.uu.se,alexander.englund@akademiska.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/lesser&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Flesser%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Flesser%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">access request email</a>\nfrom your institutional account.</p>\n\n<p>Clicking the access request email link above should open a draft email message\nin a new window, to help you provide relevant information for efficient request\nevaluation. If the above link does not work for you, then please click to view the\n<a id=\"request-email-toggle\">suggested email text</a>.</p>\n\n<div id=\"request-email\" class=\"hidden revealable small\">\n<b>To</b>: samuel.fransson@akademiska.se<br />\n<b>cc</b>: robin.strand@it.uu.se,alexander.englund@akademiska.se,aida-data@nbis.se<br />  \n<b>Subject</b>: Requesting access to dataset doi:10.23698/aida/lesser<br />\nHi!<br />\n<br />\nI work at INSTITUTION in COUNTRY, emailing from my institutional account.<br />\n<br />\nI would like to access the dataset doi:10.23698/aida/lesser, for use in ethical and legal medical diagnostics research. Could you please send me a data sharing agreement template?<br />\n<br />\nOur planned use of the data can be summarized as:<br />\n<br />\nBRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES<br />\n<br />\nDataset: https://datahub.aida.scilifelab.se/10.23698/aida/lesser<br />\n<br />\nExample agreement template: https://datahub.aida.scilifelab.se/sharing/templates/<br />\n<br />\nTemplate placeholders:<br />\n<br />\nResearch PI (\"Recipient Scientist\"):<br />\nName: PI_NAME (cc here)<br />\nTitle: PI_TITLE (ph d or better, in relevant field)<br />\n<br />\nName of institution: INSTITUTION_NAME<br />\nName of department: DEPARTMENT_NAME<br />\nInstitution postal address: POSTAL_ADDRESS<br />\n<br />\nAuthorized signatory (if other than research PI):<br />\nName: SIGNATORY_NAME (cc here)<br />\nTitle: SIGNATORY_TITLE<br />\n<br />\nThe Research PI has a PhD degree or better in a relevant field, and their institutional email address is in CC in this email conversation. The Authorized signatory is the person who signs this type of legal agreement on behalf of this institution, and their institutional email address is in CC in this conversation.<br />\n<br />\n/MY_NAME<br />\n<br />\nClick to <a href=\"mailto:samuel.fransson@akademiska.se?cc=robin.strand@it.uu.se,alexander.englund@akademiska.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/lesser&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Flesser%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Flesser%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">create draft email</a> (new window). Use your institutional account.\n</div>\n<script>\ndocument.querySelector(\"#request-email-toggle\").addEventListener('click', (e) => {\n  document.querySelector(\"#request-email\").classList.toggle('hidden')\n  })\n</script>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2022\nMedical Physics Region Uppsala, Alexander Englund, Uppsala University, Robin Strand</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Samuel Fransson and Robin Strand\n(2023)\nLow-resolution prostate MR\n<a href=\"https://doi.org/10.23698/aida/lesser\">doi:10.23698/aida/lesser</a>.</p>\n\n<p><a href=\"https://doi.org/10.1080/17453674.2021.1891512\">Samuel Fransson, David Tilly, and Robin Strand (2023) Deep learning segmentation of low-resolution images for prostate magnetic resonance-guided radiotherapy, DOI: 10.48550/arXiv.2310.11358\n</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/lnco","name":"Regional lymph node metastasis in colon adenocarcinoma","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/lnco","author":[{"name":"Gordan Maras","@id":"https://orcid.org/0000-0002-0566-6739","@type":"Person"},{"name":"Martin Lindvall","@id":"https://orcid.org/0000-0002-7014-8874","@type":"Person"},{"name":"Claes Lundstrom","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Claes Lundström","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"provider":[{"name":"Claes Lundstrom","email":"claes.lundstrom@liu.se","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Gordan Maras","email":"gordan.maras@akademiska.se","@id":"https://orcid.org/0000-0002-0566-6739","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2019-08-13","datePublished":"2019-08-13","dateModified":"2020-11-18","keywords":"Pathology, Whole slide imaging, Annotated, Lymph nodes, Cancer, Colon, Adenocarcinoma","version":"1.2.0","description":"Whole slide pathology images from regional lymph node metastasis in colon\nadenocarcinoma produced at Region Gävleborg Clinical Pathology and Cytology\ndepartment and Region Östergötland Clinical Pathology department.\nAnnotations for AI training produced as part of AIDA clinical fellowship\nproject investigating AI decision support in metastasis detection.\n\nThis dataset has been extended with a second collection series in the\n<a href=\"lnco2\">LNCO2 dataset</a> using different collection and annotation\nparameters.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/lnco#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/lnco#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":null},
    "other": {"shortName":"LNCO","origin":"Clinical","status":"Completed","annotation":"ROI boxes around lymph nodes (positive, negative or unasssed) and detailed tumor polygons\n\nSee details below.\n","countries-shared":["CN","FI","IE","NO","SE","US","SG"],"organ":[{"name":"Colon","sctid":71854001}],"age-span":null,"bytes":373662154752,"numberOfScans":977,"numberOfAnnotations":7379,"resolution":"20x and 40x","modality":["SM"],"scanner":["Aperio Scanscope (20x)","Hamamatsu NanoZoomer (40x)"],"stain":"Hematoxylin and eosin.","phase":null,"image":null,"exampleImage":[{"title":"Overview of whole slide imaging with hematoxylin and eosin staining.","url":"/assets/images/10.23698/aida/lnco/he-overview.jpeg","thumbnail-url":"/assets/images/10.23698/aida/lnco/he-overview-thumbnail.jpeg"},{"title":"To-scale view of pixel resolution in original whole slide imaging data from hematoxylin and eosin staining.","url":"/assets/images/10.23698/aida/lnco/he-to-scale.jpeg","thumbnail-url":"/assets/images/10.23698/aida/lnco/he-to-scale-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"annotation-details\">Annotation details</h2>\n\n<h3 id=\"labels\">Labels</h3>\n\n<p>The following labels exists:</p>\n\n<ul>\n  <li>\n    <p>roi_lgl_norm:: Region contains a lymph node section that do not contain tumor-positive areas, eg, is normal or negative. (but see also note below)</p>\n  </li>\n  <li>\n    <p>roi_lgl_unknown:: Region contains a lymph node for which ground truth has not been established.</p>\n  </li>\n  <li>\n    <p>roi_lgl_tumor:: Region contains a lymph node where at least some areas are tumor-positive areas. (Might not be annotated)</p>\n  </li>\n  <li>\n    <p>roi_lgl_exclude:: Contains lymph node that was determined to be of poor quality or contain severe artifacts from scanning. Would be excluded from clinial review (not suitable).</p>\n  </li>\n  <li>\n    <p>tumor:: region exclusively contains tumor pixels (but see also excl category below)</p>\n  </li>\n  <li>\n    <p>excl &amp; excl_artifact:: these areas should be substracted from tumor-annotated regions to gain pure-tumor pixels.</p>\n  </li>\n  <li>\n    <p>bkg: region contains only background pixels</p>\n  </li>\n</ul>\n\n<p>NOTE: <code class=\"language-plaintext highlighter-rouge\">tumor</code> annotations are not exhaustive, meaning, there might be more tumor areas in <code class=\"language-plaintext highlighter-rouge\">lgl_roi_tumor</code> lymph nodes than annotated with <code class=\"language-plaintext highlighter-rouge\">tumor</code> annotations.</p>\n\n<p>NOTE: Some <code class=\"language-plaintext highlighter-rouge\">roi_lgl_norm</code> areas contain tumor cells that are from an accidental contamination of the glass during processing. This is normal during routine clinical work and a challenge that automated systems should deal with in an appropriate manner. This is a very easy task for human pathologists to discern.</p>\n\n<p>NOTE: <code class=\"language-plaintext highlighter-rouge\">tumor</code> regions not within a <code class=\"language-plaintext highlighter-rouge\">roi_lgl_*</code> region should be assumed to be annotations of tumor in the the primary tumor. This can easily be verified visually, and the primary tumor is always on the initial blocks of the case (A..B…C etc)</p>\n\n<h3 id=\"sampling-procedure\">Sampling procedure</h3>\n\n<p>Sampling procedure: Query for patients with confirmed adenocarcinomas that underwent colorectomy with subsequent lymphnode review as part of TNM-staging. Query selected N cases with a relatively high number of reported positive lymph nodes.</p>\n\n<p>Source: Two medical clinics in Sweden.</p>\n\n<h3 id=\"descriptive-statistics\">Descriptive statistics</h3>\n\n<div class=\"language-plaintext highlighter-rouge\"><div class=\"highlight\"><pre class=\"highlight\"><code>LNCO1\n  patients: 39\n  cases: 39\n  images: 977\n     median dimensions(WxH px): 49799 x 38729\n     median resolution (micrometer per pixel): 0.4959\n  annotations:\n    number: 7379\n    lymph node sections (roi) 1557\n      which are negative 712\n      which are positive 292\n      which are unassessed 525\n    images with at least one detailed tumor annotation: 165\n</code></pre></div></div>\n<h2 id=\"file-formats\">File formats</h2>\n<h3 id=\"pixel-position-scaling\">Pixel position scaling</h3>\n<p>Coordinates given are relative to the image <em>width</em>. To get the correct pixel\nposition, X coordinates (and Y coordinates!) should therefore be multiplied with\nthe image <em>width</em>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/lnco\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2019\nLinköping University, Claes Lundström</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Gordan Maras, Martin Lindvall, and Claes Lundstrom\n(2019)\nRegional lymph node metastasis in colon adenocarcinoma\n<a href=\"https://doi.org/10.23698/aida/lnco\">doi:10.23698/aida/lnco</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/lnco2","name":"Regional lymph node metastasis in colon adenocarcinoma, second collection series","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/lnco2","author":[{"name":"Gordan Maras","@id":"https://orcid.org/0000-0002-0566-6739","@type":"Person"},{"name":"Martin Lindvall","@id":"https://orcid.org/0000-0002-7014-8874","@type":"Person"},{"name":"Claes Lundstrom","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2020,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Claes Lundström","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"}],"provider":[{"name":"Claes Lundstrom","email":"claes.lundstrom@liu.se","@id":"https://orcid.org/0000-0002-9368-0177","@type":"Person"},{"name":"Gordan Maras","email":"gordan.maras@akademiska.se","@id":"https://orcid.org/0000-0002-0566-6739","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2020-01-09","datePublished":"2020-01-09","dateModified":"2020-11-18","keywords":"Pathology, Annotated, Whole slide imaging, Lymph nodes, Cancer, Colon, Adenocarcinoma","version":"1.2.0","description":"Whole slide pathology images from regional lymph node metastasis in colon\nadenocarcinoma produced at Region Gävleborg Clinical Pathology and Cytology\ndepartment. Consists of fifty chronologically consecutive cases.\n\nThis dataset represents a second collection series in connection to the\n<a href=\"lnco\">LNCO dataset</a> using different collection and annotation\nparameters.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/lnco2#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/lnco2#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":null},
    "other": {"shortName":"LNCO2","origin":"Clinical","status":"Completed","annotation":"Lymph nodes have been identified by an experienced pathologist and annotated\nusing region-of-interest boxes (positive, negative, unassested). A few detailed polygons of tumor exist. See details below.\n","countries-shared":["CN","DE","FI","IE","KR","NO","SE","US","SG"],"organ":[{"name":"Colon","sctid":71854001}],"age-span":null,"bytes":651761287168,"numberOfScans":1245,"numberOfAnnotations":2598,"resolution":"20x and 40x","modality":["SM"],"scanner":["Aperio Scanscope (20x)","Hamamatsu NanoZoomer (40x)"],"stain":"Hematoxylin and eosin.","phase":null,"image":null,"exampleImage":[{"title":"Overview of lymph node whole slide imaging with hematoxylin and eosin staining.","url":"/assets/images/10.23698/aida/lnco2/lymph-nodes.jpeg","thumbnail-url":"/assets/images/10.23698/aida/lnco2/lymph-nodes-thumbnail.jpeg"},{"title":"To-scale view of pixel resolution in original lymph node whole slide imaging data from hematoxylin and eosin staining.","url":"/assets/images/10.23698/aida/lnco2/lymph-nodes-to-scale.jpeg","thumbnail-url":"/assets/images/10.23698/aida/lnco2/lymph-nodes-to-scale-thumbnail.jpeg"},{"title":"Overview of primary tumor whole slide imaging with hematoxylin and eosin staining.","url":"/assets/images/10.23698/aida/lnco2/primary-tumor.jpeg","thumbnail-url":"/assets/images/10.23698/aida/lnco2/primary-tumor-thumbnail.jpeg"},{"title":"To-scale view of pixel resolution in original primary tumor whole slide imaging data from hematoxylin and eosin staining.","url":"/assets/images/10.23698/aida/lnco2/primary-tumor-to-scale.jpeg","thumbnail-url":"/assets/images/10.23698/aida/lnco2/primary-tumor-to-scale-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"annotation-details\">Annotation details</h2>\n\n<h3 id=\"labels\">Labels</h3>\n\n<p>The following labels exists:</p>\n\n<ul>\n  <li>\n    <p>roi_lgl_norm:: Region contains a lymph node section that do not contain tumor-positive areas, eg, is normal or negative. (but see also note below)</p>\n  </li>\n  <li>\n    <p>roi_lgl_unknown:: Region contains a lymph node for which ground truth has not been established.</p>\n  </li>\n  <li>\n    <p>roi_lgl_tumor:: Region contains a lymph node where at least some areas are tumor-positive areas. (Might not be annotated)</p>\n  </li>\n  <li>\n    <p>roi_lgl_exclude:: Contains lymph node that was determined to be of poor quality or contain severe artifacts from scanning. Would be excluded from clinial review (not suitable).</p>\n  </li>\n  <li>\n    <p>roi_tumor:: Region mostly contains positive pixels, but not guaranteed that all pixels are positive.</p>\n  </li>\n  <li>\n    <p>excl &amp; excl_artifact:: these areas should be substracted from tumor-annotated regions to gain pure-tumor pixels.</p>\n  </li>\n  <li>\n    <p>bkg: region contains only background pixels</p>\n  </li>\n</ul>\n\n<p>NOTE: <code class=\"language-plaintext highlighter-rouge\">roi_tumor</code> annotations are not exhaustive, meaning, there might be more tumor areas in <code class=\"language-plaintext highlighter-rouge\">lgl_roi_tumor</code> lymph nodes than annotated with <code class=\"language-plaintext highlighter-rouge\">roi_tumor</code> annotations.</p>\n\n<p>NOTE: Some <code class=\"language-plaintext highlighter-rouge\">roi_lgl_norm</code> areas contain tumor cells that are from an accidental contamination of the glass during processing. This is normal during routine clinical work and a challenge that automated systems should deal with in an appropriate manner. This is a very easy task for human pathologists to discern.</p>\n\n<h3 id=\"sampling-procedure\">Sampling procedure</h3>\n\n<p>Sampling procedure: Query for patients with confirmed adenocarcinomas that underwent colorectomy with subsequent lymphnode review as part of TNM-staging. Selected 50 chronologically consecutive cases from unique patients (no patient has more than one case).</p>\n\n<p>Source: One medical clinic in Sweden. Same as for LNCO1.</p>\n\n<h3 id=\"descriptive-statistics\">Descriptive statistics</h3>\n\n<div class=\"language-plaintext highlighter-rouge\"><div class=\"highlight\"><pre class=\"highlight\"><code>LNCO2\n  patients: 50\n  cases: 50\n  images: 1245\n     median dimensions(WxH px): 49920 x 38016\n     median resolution (micrometer per pixel): 0.459896982\n  annotations:\n    number: 2598\n    lymph node sections (roi) 2551\n      which are negative 948\n      which are positive 75\n      which are unassessed 1517\n    images with at least one approximate tumor annotation: 30\n</code></pre></div></div>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/lnco2\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2020\nLinköping University, Claes Lundström</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Gordan Maras, Martin Lindvall, and Claes Lundstrom\n(2020)\nRegional lymph node metastasis in colon adenocarcinoma, second collection series\n<a href=\"https://doi.org/10.23698/aida/lnco2\">doi:10.23698/aida/lnco2</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/lund-probe","name":"LUND-PROBE - LUND Prostate Radiotherapy Open Benchmarking and Evaluation dataset","about":"Radiology/Radiotherapy","url":"https://datahub.aida.scilifelab.se/10.23698/aida/lund-probe","author":[{"name":"Viktor Rogowski","@type":"Person"},{"name":"Lars E Olsson","@type":"Person"},{"name":"Jonas Scherman","@type":"Person"},{"name":"Emilia Persson","@type":"Person"},{"name":"Mustafa Kadhim","@type":"Person"},{"name":"Sacha af Wetterstedt","@type":"Person"},{"name":"Adalsteinn Gunnlaugsson","@type":"Person"},{"name":"Martin Nilsson","@type":"Person"},{"name":"Nandor Vass","@type":"Person"},{"name":"Mathieu Moreau","@type":"Person"},{"name":"Maria Gebre Medhin","@type":"Person"},{"name":"Sven Bäck","@type":"Person"},{"name":"Per Munck af Rosenschöld","@type":"Person"},{"name":"Silke Engelholm","@type":"Person"},{"name":"Christian Jamtheim Gustafsson","@id":"https://orcid.org/0000-0003-2931-5615","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2025,"copyrightHolder":[{"name":"Skånes Universitetssjukhus","url":"https://vard.skane.se/skanes-universitetssjukhus-sus/","@type":"Organization"},{"name":"Christian Jamtheim Gustafsson","@id":"https://orcid.org/0000-0003-2931-5615","@type":"Person"}],"provider":[{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"},{"name":"Christian Jamtheim Gustafsson","email":"Christian.JamtheimGustafsson@skane.se","@id":"https://orcid.org/0000-0003-2931-5615","@type":"Person"},{"name":"Lars E Olsson","email":"lars_e.olsson@med.lu.se","@type":"Person"},{"name":"Rogowski Viktor","email":"Viktor.Rogowski@skane.se","@type":"Person"}],"dateCreated":"2025-01-13","datePublished":"2025-01-15","dateModified":"2025-01-15","keywords":"MRI, Synthetic CT, OAR, Radiology, Radiotherapy, Inter-observer, Target, Radiation therapy, MRI only, Delineation uncertainty, Deep learning, Annotated","version":"1.0.0","description":"Radiotherapy treatment for prostate cancer relies on computed tomography (CT) and/or magnetic resonance imaging (MRI) for delineation of radiation targets and organs at risk (OARs). Manual delineation of these volumes is regarded as the gold standard for ground truth in machine learning applications but to acquire such data is tedious and time-consuming. A publicly available clinical dataset is introduced comprising MRI images, synthetic CT (sCT) images, target and OARs delineations, and radiotherapy dose distributions for 432 prostate cancer patients treated with an MRI-only radiotherapy workflow. An extended dataset with 35 patients is also included, containing the data mentioned above together with deep learning (DL)-generated delineations, DL uncertainty maps, and DL structures manually edited by four radiation oncologists. The publication of these resources aims to aid research within the fields of automated radiotherapy planning and structure delineation, inter-observer analyses, and DL uncertainty investigation.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/lund-probe#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/lund-probe#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.1038/s41597-025-04954-5","name":"Rogowski, V. et al. LUND-PROBE – LUND Prostate Radiotherapy Open Benchmarking and Evaluation dataset. Sci Data 12, 611 (2025)."}]},
    "other": {"shortName":"LUND-PROBE","origin":"Clinical","status":"Completed","annotation":"Structures delineated from clinical radiotherapy of prostate cancer patients.\n","countries-shared":["AT","BE","CA","CN","CH","CL","FR","GB","HU","JP","MT","SE","TH","US"],"organ":[{"name":"Prostate","sctid":41216001},{"name":"Bladder"},{"name":"Body"},{"name":"CTV"},{"name":"PTV"},{"name":"Femoral Heads"},{"name":"Genitalia"},{"name":"Fiducials"},{"name":"Penile Bulb"},{"name":"Rectum"}],"age-span":null,"bytes":176562700206,"numberOfScans":467,"numberOfAnnotations":8873,"resolution":"0.6x0.7 to 0.8x0.9 mm in plane. 2.5 mm slice thickness.","modality":["MR","Synthetic CT"],"scanner":["3T Architect, GE Healthcare, Spectronic"],"stain":null,"phase":null,"image":"/assets/images/10.23698/aida/lund-probe/MRI+Struct-thumbnail.png","exampleImage":[{"title":"MRI volume with radiotherapy structures overlayed.","url":"/assets/images/10.23698/aida/lund-probe/MRI+Struct.png","thumbnail-url":"/assets/images/10.23698/aida/lund-probe/MRI+Struct-thumbnail.png"},{"title":"Synthetic CT (sCT) with radiotherapy structures and planned dose distribution overlayed.","url":"/assets/images/10.23698/aida/lund-probe/sCT+struct+Dose+colorwash.png","thumbnail-url":"/assets/images/10.23698/aida/lund-probe/sCT+struct+Dose+colorwash-thumbnail.png"},{"title":"Left: T2w MRI with prostate delineation. Middle: Four oncologist individual prostate delineations on T2w MRI zoomed in, visualized in separate colors. Right: Deep Learning segmentation uncertainty map visualized in color.","url":"/assets/images/10.23698/aida/lund-probe/uncPlot.png","thumbnail-url":"/assets/images/10.23698/aida/lund-probe/uncPlot-thumbnail.png"}]},
    "additional": "<h2 id=\"kernels\">Kernels</h2>\n\n<p>Code examples for how to load and visualize the LUND-PROBE data can be found at <a href=\"https://github.com/jamtheim/LUND-PROBE\">https://github.com/jamtheim/LUND-PROBE</a>. Feel free to modify the examples to suit your specific use case.</p>\n\n<h2 id=\"file-formats\">File formats</h2>\n<p>NIfTI</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/lund-probe\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2025\nSkånes Universitetssjukhus, Christian Jamtheim Gustafsson</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the purpose\nof medical diagnostics research with or without fee is hereby granted, provided that\nthe above copyright notice and this permission notice appear in all copies, and that\npublications resulting from the use of this data cite the following works:</p>\n\n<p>Viktor Rogowski, Lars E Olsson, Jonas Scherman, Emilia Persson, Mustafa Kadhim, Sacha af Wetterstedt, Adalsteinn Gunnlaugsson, Martin Nilsson, Nandor Vass, Mathieu Moreau, Maria Gebre Medhin, Sven Bäck, Per Munck af Rosenschöld, Silke Engelholm, and Christian Jamtheim Gustafsson\n(2025)\nLUND-PROBE - LUND Prostate Radiotherapy Open Benchmarking and Evaluation dataset\n<a href=\"https://doi.org/10.23698/aida/lund-probe\">doi:10.23698/aida/lund-probe</a>.</p>\n\n<p><a href=\"https://doi.org/10.1038/s41597-025-04954-5\">Rogowski, V. et al. LUND-PROBE – LUND Prostate Radiotherapy Open Benchmarking and Evaluation dataset. Sci Data 12, 611 (2025).</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/mbtst-dm","name":"Mammograms from cancer screening","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/mbtst-dm","author":[{"name":"Victor Dahlblom","@id":"https://orcid.org/0000-0002-4330-5387","@type":"Person"},{"name":"Magnus Dustler","@id":"https://orcid.org/0000-0002-5699-9664","@type":"Person"},{"name":"Sophia Zackrisson","@id":"https://orcid.org/0000-0001-5678-3882","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2019,"copyrightHolder":[{"name":"Lund University","url":"https://lu.se/","@type":"Organization"},{"name":"Sophia Zackrisson","@id":"https://orcid.org/0000-0001-5678-3882","@type":"Person"}],"provider":[{"name":"Magnus Dustler","email":"magnus.dustler@med.lu.se","@id":"https://orcid.org/0000-0002-5699-9664","@type":"Person"},{"name":"Victor Dahlblom","email":"victor.dahlblom@med.lu.se","@id":"https://orcid.org/0000-0002-4330-5387","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2019-09-12","datePublished":"2019-09-12","dateModified":"2019-09-12","keywords":"Radiology, Breast, Cancer, Mammography, MMG, MG, MAMMO, DM","version":"1.0","description":"14711 digital mammography (DM) examinations from screening, usually\nincluding two projections (mediolateral oblique and craniocaudal) of each\nbreast. Categorized cancer positive/negative. 95 cancer cases diagnosed on\nDM.\n\nPart of this dataset is directly available for inspection for partners on\nthe AIDA platform, and the rest can be made available on request.\n\nThis dataset is an anonymized excerpt from a dataset with richer associated\ndata, collected in a research project which is still ongoing. The authors\nwelcome proposals for new impactful research collaborations.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/mbtst-dm#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/mbtst-dm#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"Article","@id":"https://doi.org/10.1016/S1470-2045(18)30521-7","name":"Zackrisson S, Lång K, Rosso A, Johnson K, Dustler M, Förnvik D, Förnvik\nH, Sartor H, Tingberg A, Andersson I. One-view breast tomosynthesis\nversus two-view mammography in the Malmö Breast Tomosynthesis Screening\nTrial (MBTST): a prospective, population-based, diagnostic accuracy\nstudy. The Lancet Oncology. October 2018.\ndoi:10.1016/S1470-2045(18)30521-7\n"}]},
    "other": {"shortName":"MBTST-DM","origin":"Clinical","status":"Ongoing","annotation":"The mammography cancer screening was carried out as part of the Malmö Breast\nTomosynthesis Screening Trial (MBTST) and all women were examined with both\nmammography and one-view wide angle breast tomosynthesis. The examinations\nwere read in separate reading arms and this dataset only includes the\nresults from the mammography reading arm. Presence of cancer was determined\nby an experienced radiologist and verified by a second radiologist. Cancers\nwere verified with biopsy.\n","countries-shared":["AR","BR","DE","EG","IT","NL","SE","US"],"organ":[{"name":"Breast","sctid":76752008}],"age-span":"40-74","bytes":889058230272,"numberOfScans":14711,"numberOfAnnotations":0,"resolution":"Various, e.g. 2800 x 3500 px","modality":["MG"],"scanner":["Siemens Mammomat Inspiration"],"stain":null,"phase":null,"image":null,"exampleImage":[{"title":"Mediolateral oblique view of right breast.","url":"/assets/images/10.23698/aida/mbtst-dm/1rmlo.jpg","thumbnail-url":"/assets/images/10.23698/aida/mbtst-dm/1rmlo-thumbnail.jpg"},{"title":"Mediolateral oblique view of left breast.","url":"/assets/images/10.23698/aida/mbtst-dm/2lmlo.jpg","thumbnail-url":"/assets/images/10.23698/aida/mbtst-dm/2lmlo-thumbnail.jpg"},{"title":"Craniocaudal view of right breast.","url":"/assets/images/10.23698/aida/mbtst-dm/3rcc.jpg","thumbnail-url":"/assets/images/10.23698/aida/mbtst-dm/3rcc-thumbnail.jpg"},{"title":"Craniocaudal view of left breast.","url":"/assets/images/10.23698/aida/mbtst-dm/4lcc.jpg","thumbnail-url":"/assets/images/10.23698/aida/mbtst-dm/4lcc-thumbnail.jpg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<h3 id=\"pixel-position-scaling\">Pixel position scaling</h3>\n<p>Coordinates given are relative to the image <em>width</em>. To get the correct pixel\nposition, X coordinates (and Y coordinates!) should therefore be multiplied with\nthe image <em>width</em>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.\nPlease contact the dataset provider for terms of access.</p>\n\n<p>You are invited to send an\n<a href=\"mailto:magnus.dustler@med.lu.se?cc=victor.dahlblom@med.lu.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/mbtst-dm&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fmbtst-dm%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fmbtst-dm%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">access request email</a>\nfrom your institutional account.</p>\n\n<p>Clicking the access request email link above should open a draft email message\nin a new window, to help you provide relevant information for efficient request\nevaluation. If the above link does not work for you, then please click to view the\n<a id=\"request-email-toggle\">suggested email text</a>.</p>\n\n<div id=\"request-email\" class=\"hidden revealable small\">\n<b>To</b>: magnus.dustler@med.lu.se<br />\n<b>cc</b>: victor.dahlblom@med.lu.se,aida-data@nbis.se<br />  \n<b>Subject</b>: Requesting access to dataset doi:10.23698/aida/mbtst-dm<br />\nHi!<br />\n<br />\nI work at INSTITUTION in COUNTRY, emailing from my institutional account.<br />\n<br />\nI would like to access the dataset doi:10.23698/aida/mbtst-dm, for use in ethical and legal medical diagnostics research. Could you please send me a data sharing agreement template?<br />\n<br />\nOur planned use of the data can be summarized as:<br />\n<br />\nBRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES<br />\n<br />\nDataset: https://datahub.aida.scilifelab.se/10.23698/aida/mbtst-dm<br />\n<br />\nExample agreement template: https://datahub.aida.scilifelab.se/sharing/templates/<br />\n<br />\nTemplate placeholders:<br />\n<br />\nResearch PI (\"Recipient Scientist\"):<br />\nName: PI_NAME (cc here)<br />\nTitle: PI_TITLE (ph d or better, in relevant field)<br />\n<br />\nName of institution: INSTITUTION_NAME<br />\nName of department: DEPARTMENT_NAME<br />\nInstitution postal address: POSTAL_ADDRESS<br />\n<br />\nAuthorized signatory (if other than research PI):<br />\nName: SIGNATORY_NAME (cc here)<br />\nTitle: SIGNATORY_TITLE<br />\n<br />\nThe Research PI has a PhD degree or better in a relevant field, and their institutional email address is in CC in this email conversation. The Authorized signatory is the person who signs this type of legal agreement on behalf of this institution, and their institutional email address is in CC in this conversation.<br />\n<br />\n/MY_NAME<br />\n<br />\nClick to <a href=\"mailto:magnus.dustler@med.lu.se?cc=victor.dahlblom@med.lu.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/mbtst-dm&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fmbtst-dm%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fmbtst-dm%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">create draft email</a> (new window). Use your institutional account.\n</div>\n<script>\ndocument.querySelector(\"#request-email-toggle\").addEventListener('click', (e) => {\n  document.querySelector(\"#request-email\").classList.toggle('hidden')\n  })\n</script>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2019\nLund University, Sophia Zackrisson</p>\n\n<p>Permission to use, copy, modify, and/or distribute the data within AIDA\n(Analytic Imaging Diagnostics Arena https://medtech4health.se/aida) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing publications:</p>\n\n<p>Victor Dahlblom, Magnus Dustler, and Sophia Zackrisson\n(2019)\nMammograms from cancer screening\n<a href=\"https://doi.org/10.23698/aida/mbtst-dm\">doi:10.23698/aida/mbtst-dm</a>.</p>\n\n<p><a href=\"https://doi.org/10.1016/S1470-2045(18)30521-7\">Zackrisson S, Lång K, Rosso A, Johnson K, Dustler M, Förnvik D, Förnvik\nH, Sartor H, Tingberg A, Andersson I. One-view breast tomosynthesis\nversus two-view mammography in the Malmö Breast Tomosynthesis Screening\nTrial (MBTST): a prospective, population-based, diagnostic accuracy\nstudy. The Lancet Oncology. October 2018.\ndoi:10.1016/S1470-2045(18)30521-7\n</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/megre","name":"Multi-echo gradient echo (MEGRE)","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/megre","author":[{"name":"Christian Jamtheim Gustafsson","@id":"https://orcid.org/0000-0003-2931-5615","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2020,"copyrightHolder":[{"name":"Skånes Universitetssjukhus","url":"https://vard.skane.se/skanes-universitetssjukhus-sus/","@type":"Organization"},{"name":"Christian Jamtheim Gustafsson","@id":"https://orcid.org/0000-0003-2931-5615","@type":"Person"}],"provider":[{"name":"Christian Jamtheim Gustafsson","email":"Christian.JamtheimGustafsson@skane.se","@id":"https://orcid.org/0000-0003-2931-5615","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2020-04-27","datePublished":"2020-04-30","dateModified":"2020-04-30","keywords":"Gold fiducial marker, MRI only, Radiotherapy, MRI radiation therapy, Prostate, Cancer, Radiology, Annotated","version":"1.2.0","description":"Multi-echo gradient echo (MEGRE) MRI data with 8 different echo times\n(2.38-23.6 ms) from 326 + 40 prostate cancer patients with gold fiducial\nmarkers inserted into the prostate (train/validation + test dataset).\nA scientific paper that utilizes this dataset for deep learning has been\n[published](https://doi.org/10.1088/1361-6560/abb0f9).\nUnderlying description of the technique and its first use has been described\nin a [previous publication](https://www.ncbi.nlm.nih.gov/pubmed/28803447).\n\nThe data contains an image volume for each patient, for each echo time. The\ncenter of mass from the three inserted prostate gold fiducial markers was\nmanually defined. The ground truth label for this dataset consist of\nspherical objects with a radius of 1-12 mm, inserted in the center of mass\ndefined locations. Method in the paper uses 9 mm radius.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/megre#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/megre#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"Article","@id":"https://doi.org/10.1088/1361-6560/abb0f9","name":"Jamtheim Gustafsson et al (2020), Development and evaluation of a deep\nlearning based artificial intelligence for automatic identification of\ngold fiducial markers in an MRI-only prostate radiotherapy workflow.\nPhys. Med. Biol. doi:10.1088/1361-6560/abb0f9\n"},{"@type":"Article","@id":"https://doi.org/10.1002/mp.12516","name":"Gustafsson, C., Korhonen, J., Persson, E., Gunnlaugsson, A., Nyholm, T.\nand Olsson, L.E. (2017), Registration free automatic identification of\ngold fiducial markers in MRI target delineation images for prostate\nradiotherapy. Med. Phys., 44: 5563-5574. doi:10.1002/mp.12516\n"}]},
    "other": {"shortName":"MEGRE","origin":"Clinical","status":"Completed","annotation":"For 100 out of the 326 patients in the train/validation dataset the MEGRE\nimages were annotated in MATLAB where the center of mass (CoM) coordinates of\nthe gold fiducial marker signal voids were defined by one observer. For the\nremaining 226 of the patients in the train/validation dataset and the 40\npatients in the test dataset MEGRE images, echo number one or two was\nexported to the treatment planning system Eclipse v.15.1 where the CoM\npoints of the gold fiducial marker signal voids were defined by multiple\nobservers and exported as DICOM RT-structures. Further details on this are\nprovided in an article currently in review for publication. All fiducial\nidentifications were confirmed to be correct using the corresponding CT\nimages.\n","countries-shared":["SE","UY"],"organ":[{"name":"Prostate","sctid":41216001}],"age-span":"49-85","bytes":160305002394,"numberOfScans":366,"numberOfAnnotations":692,"resolution":"Scan resolution 2.8x1.46x1.46 mm, reconstructed to 0.47x0.47x2.8 mm. Each patient has 28-34 slices with 512x512 image matrix.","modality":["MR"],"scanner":["GE Discovery 750w 3T"],"stain":null,"phase":null,"image":"/assets/images/10.23698/aida/megre/image3-thumbnail.png","exampleImage":[{"title":"Pelvic transversal MEGRE image displaying an example of the first echo.","url":"/assets/images/10.23698/aida/megre/image1.jpg","thumbnail-url":"/assets/images/10.23698/aida/megre/image1-thumbnail.png"},{"title":"MEGRE images obtained using eight echo times, from 2.38 to 23.6 ms, for two different patients.","url":"/assets/images/10.23698/aida/megre/image2.png","thumbnail-url":"/assets/images/10.23698/aida/megre/image2-thumbnail.png"},{"title":"The 3D binary mask viewed as an image segmentation overlaid on the MEGRE images, seen in orthogonal views for echo 1.","url":"/assets/images/10.23698/aida/megre/image3.png","thumbnail-url":"/assets/images/10.23698/aida/megre/image3-thumbnail.png"}]},
    "additional": "<h2 id=\"kernels\">Kernels</h2>\n<p>See github repository for pre-processing and method source code</p>\n\n<p><a href=\"https://github.com/jamtheim/MEGRE-Net\">https://github.com/jamtheim/MEGRE-Net</a></p>\n\n<h2 id=\"file-formats\">File formats</h2>\n<p>Compressed NIfTI (.nii.gz) file format for both images and ground truth segmentations. The data contains an image volume for each patient, for each echo time.</p>\n\n<p>Data augmentation was performed for each of the 326 patients with random image rotations in an interval between -15 to 15 degrees around the superior-inferior patient axis using linear interpolation. Image data for each echo for each patient time was handled separately but subjected to the same amount of rotation. The same rotation was applied to the ground truth labels using nearest neighbor interpolation (to avoid producing non-binary mask values). The augmented data and labels for each patient data was saved as a new subject, producing a total of 652 subjects in the train/validation dataset, which equaled a total of 1946 fiducial objects. No data augmentation was performed for the test data set containing 40 patients.</p>\n\n<p>All image data for all echos in all datasets was independently N4 bias field corrected in an image pre-processing pipeline.</p>\n\n<p>Train/validation data set and ground truth label:<br />\nXXXXXXXXX = Real patients<br />\nXXXXXXXXXAug = Augmented data</p>\n\n<p>Test data set and ground truth label:<br />\nXXXXXXXXXtest= real patients</p>\n\n<p>One patient had four fiducial markers inserted and was excluded in the deep learning study (in review). This patient has suffix _4fid in its name. Each patient volume for each echo in test data set was subjected to Z-score normalization after N4 bias field correction.</p>\n\n<p>Folder names:<br />\nPatients40processedN4v2Normalized for Test Data<br />\nPatients326processedPooledAugN4v2 for Training/Validation Data</p>\n\n<p>Folder structure for image files:<br />\necho_1/ XXXXXXXXX_echo-1.nii.gz<br />\necho_2/ XXXXXXXXX_echo-2.nii.gz<br />\n…<br />\necho_8/ XXXXXXXXX_echo-8-nii.gz</p>\n\n<p>Folder structure for ground truth files:<br />\nGT1/ XXXXXXXXX_coords.nii.gz<br />\nGT2/ XXXXXXXXX_coords.nii.gz<br />\n…</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.\nPlease contact the dataset provider for terms of access.</p>\n\n<p>You are invited to send an\n<a href=\"mailto:Christian.JamtheimGustafsson@skane.se?cc=aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/megre&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fmegre%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0AWe%20are%20aware%20that%20publications%20resulting%20from%20the%20use%20of%20this%20data%20must%20include%20indicated%20authors%20of%20this%20dataset%20in%20the%20author%20list.%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fmegre%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">access request email</a>\nfrom your institutional account.</p>\n\n<p>Clicking the access request email link above should open a draft email message\nin a new window, to help you provide relevant information for efficient request\nevaluation. If the above link does not work for you, then please click to view the\n<a id=\"request-email-toggle\">suggested email text</a>.</p>\n\n<div id=\"request-email\" class=\"hidden revealable small\">\n<b>To</b>: Christian.JamtheimGustafsson@skane.se<br />\n<b>cc</b>: aida-data@nbis.se<br />  \n<b>Subject</b>: Requesting access to dataset doi:10.23698/aida/megre<br />\nHi!<br />\n<br />\nI work at INSTITUTION in COUNTRY, emailing from my institutional account.<br />\n<br />\nI would like to access the dataset doi:10.23698/aida/megre, for use in ethical and legal medical diagnostics research. Could you please send me a data sharing agreement template?<br />\n<br />\nOur planned use of the data can be summarized as:<br />\n<br />\nBRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES<br />\n<br />\nWe are aware that publications resulting from the use of this data must include indicated authors of this dataset in the author list.<br />\n<br />\nDataset: https://datahub.aida.scilifelab.se/10.23698/aida/megre<br />\n<br />\nExample agreement template: https://datahub.aida.scilifelab.se/sharing/templates/<br />\n<br />\nTemplate placeholders:<br />\n<br />\nResearch PI (\"Recipient Scientist\"):<br />\nName: PI_NAME (cc here)<br />\nTitle: PI_TITLE (ph d or better, in relevant field)<br />\n<br />\nName of institution: INSTITUTION_NAME<br />\nName of department: DEPARTMENT_NAME<br />\nInstitution postal address: POSTAL_ADDRESS<br />\n<br />\nAuthorized signatory (if other than research PI):<br />\nName: SIGNATORY_NAME (cc here)<br />\nTitle: SIGNATORY_TITLE<br />\n<br />\nThe Research PI has a PhD degree or better in a relevant field, and their institutional email address is in CC in this email conversation. The Authorized signatory is the person who signs this type of legal agreement on behalf of this institution, and their institutional email address is in CC in this conversation.<br />\n<br />\n/MY_NAME<br />\n<br />\nClick to <a href=\"mailto:Christian.JamtheimGustafsson@skane.se?cc=aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/megre&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fmegre%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0AWe%20are%20aware%20that%20publications%20resulting%20from%20the%20use%20of%20this%20data%20must%20include%20indicated%20authors%20of%20this%20dataset%20in%20the%20author%20list.%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fmegre%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">create draft email</a> (new window). Use your institutional account.\n</div>\n<script>\ndocument.querySelector(\"#request-email-toggle\").addEventListener('click', (e) => {\n  document.querySelector(\"#request-email\").classList.toggle('hidden')\n  })\n</script>\n\n<h3 id=\"aida-by-ca-license\">AIDA BY CA license</h3>\n<p>Copyright\n2020\nSkånes Universitetssjukhus, Christian Jamtheim Gustafsson</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p><a href=\"https://doi.org/10.1088/1361-6560/abb0f9\">Jamtheim Gustafsson et al (2020), Development and evaluation of a deep\nlearning based artificial intelligence for automatic identification of\ngold fiducial markers in an MRI-only prostate radiotherapy workflow.\nPhys. Med. Biol. doi:10.1088/1361-6560/abb0f9\n</a></p>\n\n<p>Christian Jamtheim Gustafsson\n(2020)\nMulti-echo gradient echo (MEGRE)\n<a href=\"https://doi.org/10.23698/aida/megre\">doi:10.23698/aida/megre</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/melmet","name":"Melanoma metastatic prediction dataset","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/melmet","author":[{"name":"Noora Neittaanmäki","@id":"https://orcid.org/0000-0002-8733-5510","@type":"Person"},{"name":"Filip Dahlen","@id":"https://orcid.org/0009-0000-8849-1550","@type":"Person"},{"name":"Ivan Shjuski","@id":"","@type":"Person"},{"name":"Filmon Yacob","@id":"https://orcid.org/0000-0003-3283-5670","@type":"Person"},{"name":"Ida Häggström","@id":"https://orcid.org/0000-0001-9178-6683","@type":"Person"},{"name":"Ilkka Polonen","@id":"https://orcid.org/0000-0002-5129-7364","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2025,"copyrightHolder":[{"name":"Sahlgrenska University hospital","url":"https://www.sahlgrenska.se//","@type":"Organization"},{"name":"University of Gothenburg","url":"https://www.gu.se//","@type":"Organization"},{"name":"Noora Neittaanmäki","@id":"https://orcid.org/0000-0002-8733-5510","@type":"Person"}],"provider":[{"name":"Noora Neittaanmäki","email":"noora.neittaanmaki@vgregion.se","@id":"https://orcid.org/0000-0002-8733-5510","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2025-06-09","datePublished":"2026-03-24","dateModified":"2026-03-24","keywords":"Pathology, Whole slide imaging, Weakly annotated, Skin cancer, Melanoma, Cutaneous melanoma, Staging, Metastatic prediction, WSI","version":"1.0.0","description":"Whole slide pathology images from excision specimens of primary cutaneous melanoma collected at the Departments of Pathology in the Region Västra Götaland, Sweden. The dataset contains 426 WSIs representing 426 excised primary cutaneous melanomas (249 metastatic and 177 non-metastatic). Additional information describing the histological features as text embeddings and information weather the tumor have metastasized is available as separate Excel files.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/bccc#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research. \n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/bccc#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution and co-authorship."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.1038/s41598-026-45588-w","name":"Dahlén F, Shujski I, Yacob F, Häggström I, Jovanovic J, Dudina O, Pölönen I, Neittaanmäki N. Early detection of metastatic risk in primary cutaneous melanoma using weakly supervised learning. Sci Rep. 2026 Apr 1;16(1):11234. doi: 10.1038/s41598-026-45588-w. PMID: 41922451; PMCID: PMC13046822."}]},
    "other": {"shortName":"MelMet","origin":"Clinical","status":"Completed","annotation":"The WSIs are weakly annotated on a slide level to metastatic \n(1) or non-metastatic (0). The information is available in the \nExcel files.\n","countries-shared":[],"organ":[{"name":"Skin","sctid":39937001}],"age-span":"2016-2024","bytes":1450000000000,"numberOfScans":426,"numberOfAnnotations":426,"resolution":"x40","modality":["SM"],"scanner":["NanoZoomer S360 Hamamatsu"],"stain":"H&E (hematoxylin and eosin)","phase":null,"image":"/assets/images/10.23698/aida/melmet/data-browser-thumbnail.jpg","exampleImage":[{"title":"Sample image 1","url":"/assets/images/10.23698/aida/melmet/sample-figure-1.jpg","thumbnail-url":"/assets/images/10.23698/aida/melmet/sample-figure-1-thumbnail.jpg"},{"title":"Sample image 2","url":"/assets/images/10.23698/aida/melmet/sample-figure-2.jpg","thumbnail-url":"/assets/images/10.23698/aida/melmet/sample-figure-2-thumbnail.jpg"},{"title":"Sample image 3","url":"/assets/images/10.23698/aida/melmet/sample-figure-3.jpg","thumbnail-url":"/assets/images/10.23698/aida/melmet/sample-figure-3-thumbnail.jpg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>Histopathological slides are stored as .ndpi (size per slide 1.3-5.5GB).</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/melmet\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2025\nSahlgrenska University hospital, University of Gothenburg, Noora Neittaanmäki</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the purpose\nof medical diagnostics research with or without fee is hereby granted, provided that\nthe above copyright notice and this permission notice appear in all copies, and that\npublications resulting from the use of this data cite the following works:</p>\n\n<p>Noora Neittaanmäki, Filip Dahlen, Ivan Shjuski, Filmon Yacob, Ida Häggström, and Ilkka Polonen\n(2026)\nMelanoma metastatic prediction dataset\n<a href=\"https://doi.org/10.23698/aida/melmet\">doi:10.23698/aida/melmet</a></p>\n\n<p><a href=\"https://doi.org/10.1038/s41598-026-45588-w\">Dahlén F, Shujski I, Yacob F, Häggström I, Jovanovic J, Dudina O, Pölönen I, Neittaanmäki N. Early detection of metastatic risk in primary cutaneous melanoma using weakly supervised learning. Sci Rep. 2026 Apr 1;16(1):11234. doi: 10.1038/s41598-026-45588-w. PMID: 41922451; PMCID: PMC13046822.</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/micromen","name":"Coregistered H&E- and VEGF-stained histology slides with diffusion tensor imaging data at 200 μm resolution in meningioma tumors","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/micromen","author":[{"name":"Jan Brabec","@id":"https://orcid.org/0000-0002-5826-7424","@type":"Person"},{"name":"Elisabet Englund","@id":"https://orcid.org/0000-0002-2708-2443","@type":"Person"},{"name":"Johan Bengzon","@id":"https://orcid.org/0000-0001-6536-2107","@type":"Person"},{"name":"Filip Szczepankiewicz","@id":"https://orcid.org/0000-0002-5251-587X","@type":"Person"},{"name":"Danielle van Westen","@id":"https://orcid.org/0000-0001-8649-9874","@type":"Person"},{"name":"Pia C Sundgren","@id":"https://orcid.org/0000-0001-9237-1236","@type":"Person"},{"name":"Markus Nilsson","@id":"https://orcid.org/0000-0002-3140-8223","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2023,"copyrightHolder":[{"name":"Lund University","url":"https://www.lunduniversity.lu.se/","@type":"Organization"},{"name":"Markus Nilsson","@id":"https://orcid.org/0000-0002-3140-8223","@type":"Person"}],"provider":[{"name":"Jan Brabec","email":"brabec.jan@protonmail.com","@id":"https://orcid.org/0000-0002-5826-7424","@type":"Person"},{"name":"Markus Nilsson","email":"markus.nilsson@med.lu.se","@id":"https://orcid.org/0000-0002-3140-8223","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2023-02-07","datePublished":"2023-02-14","dateModified":"2023-02-14","keywords":"Radiology, Microstructural features, Mean diffusivity, Fractional anisotropy, cCell density, Cellularity, Meningioma, Coregistration, Hematoxylin & eosin, VEGF","version":"1.0.0","description":"Mean diffusivity (MD) and fractional anisotropy (FA) obtained with diffusion tensor imaging (DTI) have been associated with cell density and tissue anisotropy across tumors, but these associations have been challenged at the microscopic level and several additional histological features have been suggested as contributing to MD and FA.\nTo facilitate investigation of the biological underpinnings of DTI parameters, we performed ex-vivo dMRI at 200 μm isotropic resolution on 16 excised meningioma tumor samples. The samples together span a variety of microstructural features: six different meningioma types and two different grades. Diffusion tensor imaging (DTI) was used to produce maps such as MD, FA, in-plane FA (FAIP), axial diffusivity (AD) or radial diffusivity (RD). The maps were coregistered to H&E (hematoxylin & eosin) and VEGF-stained histological slides.\n\nIn this repository, we provide raw and analysed DTI maps coregistered to H&E- and VEGF-stained histology slides, as well as an example analysis of the data that aims to quantify the degree to which cell density (CD), structure anisotropy (SA), as determined from histology, in comparison with convolutional neural network (CNN) account for the intra-tumor variability of MD and FAIP in meningioma tumors. The pipeline used to process the raw DTI data and the coregistration tools are hosted by [GitHub](https://github.com/jan-brabec/microimaging_histology_DIB) and the code related to the our example analysis are available [here](https://github.com/jan-brabec/microimaging_vs_histology_in_meningeomas). Please refer and cite our two journal articles mentioned in the section References below for further information on the processing and if you find this data useful.\nWe hope that data can be used in research and education concerning the link between the meningioma microstructure and parameters obtained by diffusion MRI.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/micromen#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/micromen#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution and co-authorship."}],"citation":null},
    "other": {"shortName":"MICROMEN","origin":"Clinical","status":"Completed","annotation":"Histology slides coregistered by landmark-based approach with DTI images of meningioma tumor samples.\n","countries-shared":["CZ","SE","US"],"organ":[{"name":"Brain","sctid":12738006}],"age-span":" ","bytes":390056006423,"numberOfScans":16,"numberOfAnnotations":0,"resolution":"Histology slides 0.5 µm ⤫ 0.5 µm. DTI images: 200 µm x 200 µm x 200 µm.","modality":["MR"],"scanner":["Bruker 9.4 T BioSpec Avance III MRI scanner","Microscope slide scanner Hamamatsu NanoZoomer S360","The data processed with an in-house DTI pipeline and registration tool available at repositories listed in Kernels"],"stain":"Hematoxylin & Eosin (H&E) and VEGF","phase":null,"image":"/assets/images/10.23698/aida/micromen/sample1-thumbnail.jpeg","exampleImage":[{"title":"Diffusion MRI images were coregistered to histology slides.","url":"/assets/images/10.23698/aida/micromen/sample1.jpeg","thumbnail-url":"/assets/images/10.23698/aida/micromen/sample1-thumbnail.jpeg"},{"title":"Overview of the H&E-stained meningioma histopathology of all sixteen samples.","url":"/assets/images/10.23698/aida/micromen/sample2.jpeg","thumbnail-url":"/assets/images/10.23698/aida/micromen/sample2-thumbnail.jpeg"},{"title":"Overview of the VEGF-stained meningioma histopathology of all sixteen samples.","url":"/assets/images/10.23698/aida/micromen/sample3.jpeg","thumbnail-url":"/assets/images/10.23698/aida/micromen/sample3-thumbnail.jpeg"},{"title":"Overview of the coregistered data (sample 10).","url":"/assets/images/10.23698/aida/micromen/sample4.jpeg","thumbnail-url":"/assets/images/10.23698/aida/micromen/sample4-thumbnail.jpeg"}]},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>Histology slides: .tif and .mat files.\nDTI images: .nii and .mat files.</p>\n\n<h2 id=\"kernels\">Kernels</h2>\n<p>The pipeline used to process the raw DTI data and the coregistration tools are available at <a href=\"https://github.com/jan-brabec/microimaging_histology_DIB\">https://github.com/jan-brabec/microimaging_histology_DIB</a></p>\n\n<p>The code related to the our example analysis are available at <a href=\"https://github.com/jan-brabec/microimaging_vs_histology_in_meningeomas\">https://github.com/jan-brabec/microimaging_vs_histology_in_meningeomas</a>.</p>\n\n<h2 id=\"file-formats-1\">File formats</h2>\n<h3 id=\"pixel-position-scaling\">Pixel position scaling</h3>\n<p>Coordinates given are relative to the image <em>width</em>. To get the correct pixel\nposition, X coordinates (and Y coordinates!) should therefore be multiplied with\nthe image <em>width</em>.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.\nPlease contact the dataset provider for terms of access.</p>\n\n<p>You are invited to send an\n<a href=\"mailto:brabec.jan@protonmail.com?cc=markus.nilsson@med.lu.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/micromen&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fmicromen%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fmicromen%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">access request email</a>\nfrom your institutional account.</p>\n\n<p>Clicking the access request email link above should open a draft email message\nin a new window, to help you provide relevant information for efficient request\nevaluation. If the above link does not work for you, then please click to view the\n<a id=\"request-email-toggle\">suggested email text</a>.</p>\n\n<div id=\"request-email\" class=\"hidden revealable small\">\n<b>To</b>: brabec.jan@protonmail.com<br />\n<b>cc</b>: markus.nilsson@med.lu.se,aida-data@nbis.se<br />  \n<b>Subject</b>: Requesting access to dataset doi:10.23698/aida/micromen<br />\nHi!<br />\n<br />\nI work at INSTITUTION in COUNTRY, emailing from my institutional account.<br />\n<br />\nI would like to access the dataset doi:10.23698/aida/micromen, for use in ethical and legal medical diagnostics research. Could you please send me a data sharing agreement template?<br />\n<br />\nOur planned use of the data can be summarized as:<br />\n<br />\nBRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES<br />\n<br />\nDataset: https://datahub.aida.scilifelab.se/10.23698/aida/micromen<br />\n<br />\nExample agreement template: https://datahub.aida.scilifelab.se/sharing/templates/<br />\n<br />\nTemplate placeholders:<br />\n<br />\nResearch PI (\"Recipient Scientist\"):<br />\nName: PI_NAME (cc here)<br />\nTitle: PI_TITLE (ph d or better, in relevant field)<br />\n<br />\nName of institution: INSTITUTION_NAME<br />\nName of department: DEPARTMENT_NAME<br />\nInstitution postal address: POSTAL_ADDRESS<br />\n<br />\nAuthorized signatory (if other than research PI):<br />\nName: SIGNATORY_NAME (cc here)<br />\nTitle: SIGNATORY_TITLE<br />\n<br />\nThe Research PI has a PhD degree or better in a relevant field, and their institutional email address is in CC in this email conversation. The Authorized signatory is the person who signs this type of legal agreement on behalf of this institution, and their institutional email address is in CC in this conversation.<br />\n<br />\n/MY_NAME<br />\n<br />\nClick to <a href=\"mailto:brabec.jan@protonmail.com?cc=markus.nilsson@med.lu.se,aida-data@nbis.se&amp;subject=Requesting%20access%20to%20dataset%20doi:10.23698/aida/micromen&amp;body=Hi%21%0A%0AI%20work%20at%20INSTITUTION%20in%20COUNTRY%2C%20emailing%20from%20my%20institutional%20account.%0A%0AI%20would%20like%20to%20access%20the%20dataset%20doi%3A10.23698%2Faida%2Fmicromen%2C%20for%20use%20in%20ethical%20and%20legal%20medical%20diagnostics%20research.%20Could%20you%20please%20send%20me%20a%20data%20sharing%20agreement%20template%3F%0A%0AOur%20planned%20use%20of%20the%20data%20can%20be%20summarized%20as%3A%0A%0ABRIEF_DESCRIPTION_OF_PLANNED_ACTIVITIES%0A%0ADataset%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2F10.23698%2Faida%2Fmicromen%0A%0AExample%20agreement%20template%3A%20https%3A%2F%2Fdatahub.aida.scilifelab.se%2Fsharing%2Ftemplates%2F%0A%0ATemplate%20placeholders%3A%0A%0AResearch%20PI%20%28%22Recipient%20Scientist%22%29%3A%0AName%3A%20PI_NAME%20%28cc%20here%29%0ATitle%3A%20PI_TITLE%20%28ph%20d%20or%20better%2C%20in%20relevant%20field%29%0A%0AName%20of%20institution%3A%20INSTITUTION_NAME%0AName%20of%20department%3A%20DEPARTMENT_NAME%0AInstitution%20postal%20address%3A%20POSTAL_ADDRESS%0A%0AAuthorized%20signatory%20%28if%20other%20than%20research%20PI%29%3A%0AName%3A%20SIGNATORY_NAME%20%28cc%20here%29%0ATitle%3A%20SIGNATORY_TITLE%0A%0AThe%20Research%20PI%20has%20a%20PhD%20degree%20or%20better%20in%20a%20relevant%20field%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20email%20conversation.%20The%20Authorized%20signatory%20is%20the%20person%20who%20signs%20this%20type%20of%20legal%20agreement%20on%20behalf%20of%20this%20institution%2C%20and%20their%20institutional%20email%20address%20is%20in%20CC%20in%20this%20conversation.%0A%0A%2FMY_NAME%0A\">create draft email</a> (new window). Use your institutional account.\n</div>\n<script>\ndocument.querySelector(\"#request-email-toggle\").addEventListener('click', (e) => {\n  document.querySelector(\"#request-email\").classList.toggle('hidden')\n  })\n</script>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2023\nLund University, Markus Nilsson</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the purpose\nof medical diagnostics research with or without fee is hereby granted, provided that\nthe above copyright notice and this permission notice appear in all copies, and that\npublications resulting from the use of this data cite the following works:</p>\n\n<p>Jan Brabec, Elisabet Englund, Johan Bengzon, Filip Szczepankiewicz, Danielle van Westen, Pia C Sundgren, and Markus Nilsson\n(2023)\nCoregistered H&amp;E- and VEGF-stained histology slides with diffusion tensor imaging data at 200 μm resolution in meningioma tumors\n<a href=\"https://doi.org/10.23698/aida/micromen\">doi:10.23698/aida/micromen</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-1-body","name":"SCAPIS body data from site 1","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-1-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Body, SCAPIS","description":"Data from body scans carried out in the SCAPIS study cohort in site 1. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-1-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-1-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":91722005}],"age-span":"50-64","bytes":95546382153,"numberOfScans":6108,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 161391 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-1-casc","name":"SCAPIS CASC data from Site 1","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-1-casc","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CASC scans carried out in the SCAPIS study cohort in site 1. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-1-casc#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-1-CASC","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":290780401326,"numberOfScans":6108,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 51796 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-1-ccta","name":"SCAPIS CCTA data from site 1","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-1-ccta","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CCTA scans carried out in the SCAPIS study cohort in site 1. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-1-ccta#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-1-CCTA","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":1583493685844,"numberOfScans":6108,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 3004429 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-1-lung","name":"SCAPIS lung data from site 1","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-1-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Lung, SCAPIS","description":"Data from lung scans carried out in the SCAPIS study cohort in site 1. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-1-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-1-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":39607008}],"age-span":"50-64","bytes":3579265290875,"numberOfScans":6108,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 6793762 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-2-body","name":"SCAPIS body data from site 2","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-2-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Body, SCAPIS","description":"Data from body scans carried out in the SCAPIS study cohort in site 2. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-2-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-2-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":91722005}],"age-span":"50-64","bytes":101817425967,"numberOfScans":6146,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 193246 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-2-casc","name":"SCAPIS CASC data from site 2","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-2-casc","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CASC scans carried out in the SCAPIS study cohort in site 2. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-2-casc#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-2-CASC","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":332882776809,"numberOfScans":6146,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 631570 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-2-ccta","name":"SCAPIS CCTA data from site 2","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-2-ccta","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CCTA scans carried out in the SCAPIS study cohort in site 2. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-2-ccta#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-2-CCTA","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":3246097502852,"numberOfScans":6146,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 6157244 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-2-lung","name":"SCAPIS lung data from site 2","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-2-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Lung, SCAPIS","description":"Data from lung scans carried out in the SCAPIS study cohort in site 2. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-2-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-2-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":39607008}],"age-span":"50-64","bytes":7354685658988,"numberOfScans":6146,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 13956730 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-3-body","name":"SCAPIS body data from site 3","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-3-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Body, SCAPIS","description":"Data from body scans carried out in the SCAPIS study cohort in site 3. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-3-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-3-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":91722005}],"age-span":"50-64","bytes":40349211414,"numberOfScans":4977,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 76603 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-3-casc","name":"SCAPIS CASC data from site 3","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-3-casc","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CASC scans carried out in the SCAPIS study cohort in site 3. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.  \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-3-casc#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-3-CASC","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":235608640096,"numberOfScans":4976,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 447126 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-3-ccta","name":"SCAPIS CCTA data from site 3","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-3-ccta","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CCTA scans carried out in the SCAPIS study cohort in site 3. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-3-ccta#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-3-CCTA","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":1983609709227,"numberOfScans":4976,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 3763667 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-3-lung","name":"SCAPIS lung data from site 3","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-3-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Lung, SCAPIS","description":"Data from lung scans carried out in the SCAPIS study cohort in site 3. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-3-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-3-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":39607008}],"age-span":"50-64","bytes":3674040822366,"numberOfScans":4977,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 6973765 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-4-body","name":"SCAPIS body data from site 4","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-4-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Body, SCAPIS","description":"Data from body scans carried out in the SCAPIS study cohort in site 4. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-4-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-4-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":91722005}],"age-span":"50-64","bytes":72545873084,"numberOfScans":5024,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 137648 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-4-casc","name":"SCAPIS CASC data from site 4","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-4-casc","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CASC scans carried out in the SCAPIS study cohort in site 4. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-4-casc#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-4-CASC","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":263095775414,"numberOfScans":5024,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 499066 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-4-ccta","name":"SCAPIS CCTA data from site 4","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-4-ccta","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CCTA scans carried out in the SCAPIS study cohort in site 4. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-4-ccta#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-4-CCTA","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":2701083705376,"numberOfScans":5024,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 5122645 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-4-lung","name":"SCAPIS lung data from site 4","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-4-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Lung, SCAPIS","description":"Data from lung scans carried out in the SCAPIS study cohort in site 4. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-4-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-4-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":39607008}],"age-span":"50-64","bytes":5787151514713,"numberOfScans":5032,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 10980047 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-5-body","name":"SCAPIS body data from site 5","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-5-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Body, SCAPIS","description":"Data from body scans carried out in the SCAPIS study cohort in site 5. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.  \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-5-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-5-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":91722005}],"age-span":"50-64","bytes":72443408882,"numberOfScans":4862,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 137495 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-5-casc","name":"SCAPIS CASC data from site 5","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-5-casc","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CASC scans carried out in the SCAPIS study cohort in site 5. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-5-casc#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-5-CASC","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":249704806854,"numberOfScans":4862,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 473763 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-5-ccta","name":"SCAPIS CCTA data from site 5","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-5-ccta","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CCTA scans carried out in the SCAPIS study cohort in site 5. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-5-ccta#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-5-CCTA","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":1900712166339,"numberOfScans":4862,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 3605516 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-5-lung","name":"SCAPIS lung data from site 5","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-5-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Lung, SCAPIS","description":"Data from lung scans carried out in the SCAPIS study cohort in site 5. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-5-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-5-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":39607008}],"age-span":"50-64","bytes":4012855726344,"numberOfScans":4862,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 7615479 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-6-body","name":"SCAPIS body data from site 6","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-6-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Body, SCAPIS","description":"Data from body scans carried out in the SCAPIS study cohort in site 6. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.  \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-6-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-6-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":91722005}],"age-span":"50-64","bytes":35493996203,"numberOfScans":2434,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 67382 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-6-casc","name":"SCAPIS CASC data from site 6","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-6-casc","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CASC scans carried out in the SCAPIS study cohort in site 6. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.  \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-6-casc#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-6-CASC","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":128023137739,"numberOfScans":2434,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 242958 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-6-ccta","name":"SCAPIS CCTA data from site 6","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-6-ccta","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Heart, SCAPIS","description":"Data from CCTA scans carried out in the SCAPIS study cohort in site 6. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.  \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-6-ccta#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-6-CCTA","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":80891009}],"age-span":"50-64","bytes":1435506785737,"numberOfScans":2434,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 2723883 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-ct-site-6-lung","name":"SCAPIS lung data from site 6","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-6-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2024,"copyrightHolder":[{"name":"Karolinska Institute","url":"https://ki.se/","@type":"Organization"}],"dateCreated":"2024-05-10","datePublished":"2024-05-10","dateModified":"2026-03-26","keywords":"Radiology, Computed tomography, Lung, SCAPIS","description":"Data from lung scans carried out in the SCAPIS study cohort in site 6. SCAPIS has recruited 30000 men and women aged 50 to 64 years during 2013-2018 with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm). Visit [www.scapis.org](https://www.scapis.org) for more information regarding the study.  \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-ct-site-6-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-CT-SITE-6-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":39607008}],"age-span":"50-64","bytes":3542420724480,"numberOfScans":2434,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of 7z compressed archives containing a total of 6724044 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Please contact <a href=\"mailto:scapis@scapis.org\">scapis@scapis.org</a> regarding access or details regarding the data.  AIDA <a href=\"/datasets/scapis/#access\">routines</a> for accessing SCAPIS.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-1-body","name":"SCAPIS RE-EXAMINATION-600 Body data from site 1","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-1-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from body scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 1. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-1-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-1-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":null}],"age-span":"50-64","bytes":5520837727,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 6328 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-1-heart-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart contrast data from site 1","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-1-heart-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 1. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-1-heart-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-1-HEART-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":225148058259,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 332065 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-1-lung","name":"SCAPIS RE-EXAMINATION-600 Lung data from site 1","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-1-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Lung, Scapis","description":"Data from Lung scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 1. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-1-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-1-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":null}],"age-span":"50-64","bytes":787494644009,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 770653 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-1-heart-no-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart no contrast data from Site 1","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-1-heart-no-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart no contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 1. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-1-heart-no-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-1-HEART-NO-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":12637196747,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 19305 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-2-body","name":"SCAPIS RE-EXAMINATION-600 Body data from site 2","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-2-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from body scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 2. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-1-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-2-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":null}],"age-span":"50-64","bytes":36599498473,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of  27691 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-2-heart-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart contrast data from site 2","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-2-heart-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 2. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-2-heart-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-2-HEART-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":282522931983,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 437376 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-2-lung","name":"SCAPIS RE-EXAMINATION-600 Lung data from site 2","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-2-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Lung, Scapis","description":"Data from Lung scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 2. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-2-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-2-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":null}],"age-span":"50-64","bytes":833792337337,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 768118 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-2-heart-no-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart no contrast data from Site 2","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-2-heart-no-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart no contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 2. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-2-heart-no-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-2-HEART-NO-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":12423235612,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 18979 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-3-body","name":"SCAPIS RE-EXAMINATION-600 Body data from site 3","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-3-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from body scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 3. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-3-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-3-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":null}],"age-span":"50-64","bytes":56134738141,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 43085 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-3-heart-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart contrast data from site 3","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-3-heart-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 3. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-3-heart-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-3-HEART-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":173608165645,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 253841 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-3-lung","name":"SCAPIS RE-EXAMINATION-600 Lung data from site 3","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-3-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Lung, Scapis","description":"Data from Lung scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 3. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-3-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-3-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":null}],"age-span":"50-64","bytes":986206816617,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 758388  .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-3-heart-no-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart no contrast data from Site 3","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-3-heart-no-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart no contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 3. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-3-heart-no-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-3-HEART-NO-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":12136837239,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 18444 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-4-body","name":"SCAPIS RE-EXAMINATION-600 Body data from site 4","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-4-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from body scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 4. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-4-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-4-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":null}],"age-span":"50-64","bytes":367676694,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 632 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-4-heart-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart contrast data from site 4","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-4-heart-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from HEart contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 4. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-4-heart-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-4-HEART-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":193899039015,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 292799 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-4-lung","name":"SCAPIS RE-EXAMINATION-600 Lung data from site 4","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-4-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Lung, Scapis","description":"Data from Lung scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 4. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-4-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-4-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":null}],"age-span":"50-64","bytes":643327598807,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 805725 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-4-heart-no-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart no contrast data from Site 4","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-4-heart-no-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart no contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 4. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-4-heart-no-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-4-HEART-NO-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":12220183099,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 18556 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-5-body","name":"SCAPIS RE-EXAMINATION-600 Body data from site 5","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-5-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from body scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 5. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-5-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-5-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":null}],"age-span":"50-64","bytes":330726238,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 581 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-5-heart-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart contrast data from site 5","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-5-heart-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 5. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-5-heart-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-5-HEART-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":204118289377,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 298833 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-5-lung","name":"SCAPIS RE-EXAMINATION-600 Lung data from site 5","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-5-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Lung, Scapis","description":"Data from Lung scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 5. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-5-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-5-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":null}],"age-span":"50-64","bytes":556224892868,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 747327 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-5-heart-no-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart no contrast data from Site 5","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-5-heart-no-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart no contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 5. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-5-heart-no-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-5-HEART-NO-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":12945421944,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 19632 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-6-body","name":"SCAPIS RE-EXAMINATION-600 Body data from site 6","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-6-body","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from body scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 6. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-6-body#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-6-BODY","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Body","sctid":null}],"age-span":"50-64","bytes":53993823465,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 40164  .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-6-heart-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart contrast data from site 6","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-6-heart-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart contrast scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 6. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-6-heart-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-6-HEART-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":197146849690,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 286272 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-6-lung","name":"SCAPIS RE-EXAMINATION-600 Lung data from site 6","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-6-lung","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Lung, Scapis","description":"Data from Lung scans carried out in the SCAPIS RE-EXAMINATION-600 study cohort in site 6. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-6-lung#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-6-LUNG","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Lung","sctid":null}],"age-span":"50-64","bytes":952424280107,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 718312 .dcm files</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/scapis-re-examination-600-ct-site-6-heart-no-contrast","name":"SCAPIS RE-EXAMINATION-600 Heart no contrast data from Site 6","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-6-heart-no-contrast","author":[{"name":"SCAPIS","@id":"https://www.scapis.org/","@type":"Organization"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2026,"copyrightHolder":[{"name":"","url":"","@type":"Organization"}],"dateCreated":"2026-03-19","datePublished":"2026-03-19","dateModified":"2026-03-19","keywords":"Radiology, Computed tomography, Heart, Scapis","description":"Data from Heart no contrast scans carried out in the SCAPIS study cohort in site 6. SCAPIS has recruited 25000 men and women aged 50 to 64 years with detailed imaging and functional analyses of cardiovascular and pulmonary systems. The data was collected at six university hospitals in Sweden (Uppsala, Umeå, Linköping, Malmö/Lund, Gothenburg and Stockholm).   \n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/scapis-re-examination-600-ct-site-6-heart-no-contrast#controlled-access","@type":"CreativeWork","abstract":"Please contact SCAPIS for terms of access.\n"}]},
    "other": {"modality":["CT"],"shortName":"SCAPIS-RE-EXAMINATION-600-CT-SITE-6-HEART-NO-CONTRAST","origin":"Clinical","status":"Ongoing","countries-shared":["SE"],"organ":[{"name":"Heart","sctid":null}],"age-span":"50-64","bytes":11798614565,"numberOfScans":null,"image":"/assets/images/logos/heartlungfoundation-logo.jpg"},
    "additional": "<h2 id=\"file-formats\">File formats</h2>\n<p>The dataset consists of uncompressed and 7z compressed archives containing a total of 17919 .dcm files.</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Please contact <a href=\"/datasets/scapis/#access\">SCAPIS</a> for terms of access.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/sprob20","name":"Spear Prostate Biopsy 2020 (SPROB20)","about":"Pathology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/sprob20","author":[{"name":"Peter Walhagen","@id":"https://orcid.org/0000-0002-3164-818X","@type":"Person"},{"name":"Pontus Röbeck","@id":"https://orcid.org/0000-0001-5556-117X","@type":"Person"},{"name":"Ewert Bengtsson","@id":"","@type":"Person"},{"name":"Christer Busch","@id":"","@type":"Person"},{"name":"Michael Häggman","@id":"","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2020,"copyrightHolder":[{"name":"Michael Häggman","@id":"","@type":"Person"},{"name":"Uppsala University Hospital","url":"https://www.akademiska.se/en/","@type":"Organization"}],"provider":[{"name":"Peter Walhagen","email":"peter.walhagen@spearpoint.se","@id":"https://orcid.org/0000-0002-3164-818X","@type":"Person"},{"name":"Michael Häggman","email":" michael.haggman@akademiska.se","@id":"","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2020-04-27","datePublished":"2020-04-30","dateModified":"2020-04-30","keywords":"Prostate Cancer, Pathology","version":"1.0.0","description":"2611 scanned prostate biopsies from 460 patient cases sampled between 2015 and 2018. Annotation of clinical metadata and treatment decisions made in connection with biopsy sampling exist on case-level. Roughly 35% of the biopsies contain cancer.\nIn-image annotations exists in macro images the form of ink markings from the clinical workflow.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/sprob20#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/sprob20#aida-by-ca-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":null},
    "other": {"shortName":"SPROB20","origin":"Clinical","status":"Completed","annotation":"The cases are annotated with clinical data relevant for the treatment decision and the following treatment decision made in conjunction with the biopsy sampling.\nEach image is given an identifier which can be connected to the case by the case mapping file.\nClinical data and treatment decisions have been extracted by manual medical records search. The information about treatment is what has been noted in conjunction with the diagnosis. \nSome cases contain missing data in some of the fields as the data wasn’t available. Some of the biopsies are resliced versions of another biopsy belonging to the same case. \nTogether with the images macro-images of the biopsies exist with localized annotation of gleason grade and cancer detection as provided in the clinical workflow.\n","countries-shared":["DE","FR","SE","US"],"organ":[{"name":"Prostate","sctid":41216001}],"age-span":"39 - 79 years, median 67 years","bytes":492600000000,"numberOfScans":2611,"caseLevelAnnotaions":"Treatment decision, Gleason, PIRADS, PSA, Prostate volume, clinical T-stage","imageLevelAnnotations":"Connection to use","numberOfAnnotations":null,"resolution":"0.2204 microns per pixel (40x)","modality":["SM"],"scanner":["Hamamatsu NanoZoomer S60"],"stain":"H&E","phase":null,"exampleImage":[{"title":"Example biopsy downsampled 8x","url":"/assets/images/10.23698/aida/sprob20/a.jpg","thumbnail-url":"/assets/images/10.23698/aida/sprob20/a_thumb.jpg"},{"title":"Example biopsy downsampled 8x","url":"/assets/images/10.23698/aida/sprob20/b.jpg","thumbnail-url":"/assets/images/10.23698/aida/sprob20/b_thumb.jpg"},{"title":"Example patch in full resolution","url":"/assets/images/10.23698/aida/sprob20/pa_fullres.jpg","thumbnail-url":"/assets/images/10.23698/aida/sprob20/pa_fullres_thumb.jpg"},{"title":"Macro image with annotation","url":"/assets/images/10.23698/aida/sprob20/macro_a.jpg","thumbnail-url":"/assets/images/10.23698/aida/sprob20/macro_a_thumb.jpg"}]},
    "additional": "<h2 id=\"kernels\">Kernels</h2>\n<p>Example jupyter notebook, SPROB20_sample.ipynb, for loading data from the dataset is available at</p>\n\n<p><a href=\"https://github.com/spearpoint-analytics/sprob20\">https://github.com/spearpoint-analytics/sprob20</a></p>\n\n<h2 id=\"file-formats\">File formats</h2>\n\n<p>Images: Pyramidal .tif</p>\n\n<p>Metadata: .csv</p>\n\n<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/sprob20\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2020\nMichael Häggman, Uppsala University Hospital</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the purpose\nof medical diagnostics research with or without fee is hereby granted, provided that\nthe above copyright notice and this permission notice appear in all copies, and that\npublications resulting from the use of this data cite the following works:</p>\n\n<p>Peter Walhagen, Pontus Röbeck, Ewert Bengtsson, Christer Busch, and Michael Häggman\n(2020)\nSpear Prostate Biopsy 2020 (SPROB20)\n<a href=\"https://doi.org/10.23698/aida/sprob20\">doi:10.23698/aida/sprob20</a>.</p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/sr2023","name":"Shoulder radiographs classified on both fractures according to 2018 AO/OTA and classified degenerative conditions","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/sr2023","author":[{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"},{"name":"Martin Magnéli","@id":"https://orcid.org/0000-0003-0341-0227","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2023,"copyrightHolder":[{"name":"Karolinska Institutet","url":"https://ki.se/","@type":"Organization"},{"name":"Max Gordon","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"}],"provider":[{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"},{"name":"Max Gordon","email":"max.gordon@ki.se","@id":"https://orcid.org/0000-0002-8080-5815","@type":"Person"},{"name":"Martin Magnéli","email":"martin.magneli@ki.se","@id":"https://orcid.org/0000-0003-0341-0227","@type":"Person"}],"dateCreated":"2023-06-12","datePublished":"2023-06-13","dateModified":"2023-06-13","keywords":"Pathology, Annotated, Plain radiographs, Shoulder, Clavicle, Scapula, Humerus, Fracture, Osteoarthritis, Cuff arthropathy","version":"1.0.0","description":"A dataset containing 1257 shoulder radiographs from 406 patients. Shoulder fractures in the humerus, clavicle and scapula are classified according to the 2018 AO/OTA classification. The radiographs are also classified for degenerative conditions such as osteoarthritis, avascular necrosis and cuff arthropathy. The radiographs are classified by experienced orthopaedic surgeons specialized in shoulder surgery.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/sr2023#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/sr2023#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.1371/journal.pone.0289808","name":"Magnéli M, Ling P, Gislén J, Fagrell J, Demir Y, Arverud ED, et al. (2023) Deep learning classification of shoulder fractures on plain radiographs of the humerus, scapula and clavicle. PLoS ONE 18(8): e0289808. https://doi.org/10.1371/journal.pone.0289808"}]},
    "other": {"shortName":"SR2023","origin":"Clinical","status":"Completed","annotation":"Manually annotated by experienced orthopedic surgeons.\nClassification for fractures according to 2018 AO/OTA.\nOA according to Samilson-Prieto.\nAvascular necrosis according to Cruess.\nCuff arthropathy according to Hamada.\nGlenoid according to Favard.\n","countries-shared":["DE","SE","TR"],"organ":[{"name":"Shoulder","sctid":16982005}],"age-span":"15+","bytes":2696968974,"numberOfScans":1257,"numberOfAnnotations":166,"resolution":"Various. Image sizes vary from 800x600px to 2000x1000px.","modality":["CR"],"scanner":null,"stain":null,"phase":null,"image":"/assets/images/10.23698/aida/sr2023/1-lateral-shoulder-thumbnail.png","exampleImage":[{"title":"Lateral view of a diaphyseal humerus fracture.","url":"/assets/images/10.23698/aida/sr2023/1-lateral-shoulder.png","thumbnail-url":"/assets/images/10.23698/aida/sr2023/1-lateral-shoulder-thumbnail.png"},{"title":"AP view of shoulder with OA changes, classified according to Samilson-Prieto.","url":"/assets/images/10.23698/aida/sr2023/2-shoulder-ap-view.jpg","thumbnail-url":"/assets/images/10.23698/aida/sr2023/2-shoulder-ap-view-thumbnail.jpg"},{"title":"Another AP view of a shoulder with OA.","url":"/assets/images/10.23698/aida/sr2023/3-shoulder-ap-view.jpg","thumbnail-url":"/assets/images/10.23698/aida/sr2023/3-shoulder-ap-view-thumbnail.jpg"},{"title":"Images include inplants such as arthroplasties.","url":"/assets/images/10.23698/aida/sr2023/4-shoulder-with-inplants.png","thumbnail-url":"/assets/images/10.23698/aida/sr2023/4-shoulder-with-inplants-thumbnail.png"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research.</p>\n\n<p>To request access to the dataset, use the <code class=\"language-plaintext highlighter-rouge\">Apply for access</code> button below. \nNote that the recipient researcher must hold at least a PhD degree in a\nrelevant field and that the applicant should be an authorized signatory who can\nlegally enter into data sharing agreements on the behalf of the institution.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/sr2023\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2023\nKarolinska Institutet, Max Gordon</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the\npurpose of medical diagnostics research with or without fee is hereby granted,\nprovided that the above copyright notice and this permission notice appear in\nall copies, and that publications resulting from the use of this data cite the\nfollowing works:</p>\n\n<p>Max Gordon and Martin Magnéli\n(2023)\nShoulder radiographs classified on both fractures according to 2018 AO/OTA and classified degenerative conditions\n<a href=\"https://doi.org/10.23698/aida/sr2023\">doi:10.23698/aida/sr2023</a>.</p>\n\n<p><a href=\"https://doi.org/10.1371/journal.pone.0289808\">Magnéli M, Ling P, Gislén J, Fagrell J, Demir Y, Arverud ED, et al. (2023) Deep learning classification of shoulder fractures on plain radiographs of the humerus, scapula and clavicle. PLoS ONE 18(8): e0289808. https://doi.org/10.1371/journal.pone.0289808</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/synthetic/brgandi","name":"Synthetic brain tumor images from GANs and diffusion models","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/synthetic/brgandi","author":[{"name":"Muhammad Usman Akbar","@id":"https://orcid.org/0000-0002-3248-5132","@type":"Person"},{"name":"Anders Eklund","@id":"https://orcid.org/0000-0001-7061-7995","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2023,"copyrightHolder":[{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Muhammad Usman Akbar","@id":"https://orcid.org/0000-0002-3248-5132","@type":"Person"},{"name":"Linköping University","url":"https://liu.se/","@type":"Organization"},{"name":"Anders Eklund","@id":"https://orcid.org/0000-0001-7061-7995","@type":"Person"}],"provider":[{"name":"Anders Eklund","email":"anders.eklund@liu.se","@id":"https://orcid.org/0000-0001-7061-7995","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2023-10-18","datePublished":"2023-10-18","dateModified":"2023-10-18","keywords":"Radiology, Annotated, Brain, MRI, Tumor, Synthetic, Generative, GAN, Diffusion model","version":"1.0.0","description":"This dataset is a collection of synthetic images generated by 5 generative models (Progressive GAN, StyleGAN1, StyleGAN2, StyleGAN3, diffusion model) trained on the BraTS 2020 and 2021 datasets [1,2,3,4,5] (which share MR volumes from brain tumor patients and the corresponding tumor annotations). The trained generative models are also shared in this dataset. See our recent work [6] for more information, and a comparison of training segmentation networks with real and synthetic images.\n\n**Note**: if you want to use real brain tumor images, use the [BraTS dataset](http://www.braintumorsegmentation.org/) (which we used to create these synthetic images).\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/synthetic/brgandi#controlled-access","@type":"CreativeWork","abstract":"Free for use in research or education.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/synthetic/brgandi#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.48550/arXiv.2107.02314","name":"U.Baid, et al., The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification, arXiv:2107.02314, 2021."},{"@type":"CreativeWork","@id":"https://doi.org/10.1109/tmi.2014.2377694","name":"B. H. Menze, A. Jakab, S. Bauer, J. Kalpathy-Cramer, K. Farahani, J. Kirby, et al., The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS), IEEE Transactions on Medical Imaging 34(10), 1993-2024 (2015) DOI: 10.1109/TMI.2014.2377694"},{"@type":"CreativeWork","@id":"https://doi.org/10.1038/sdata.2017.117","name":"S. Bakas, H. Akbari, A. Sotiras, M. Bilello, M. Rozycki, J.S. Kirby, et al., Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features, Nature Scientific Data, 4:170117 (2017) DOI: 10.1038/sdata.2017.117"},{"@type":"CreativeWork","@id":"https://doi.org/10.7937/K9/TCIA.2017.KLXWJJ1Q","name":"S. Bakas, H. Akbari, A. Sotiras, M. Bilello, M. Rozycki, J. Kirby, et al., Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-GBM collection, The Cancer Imaging Archive, 2017. DOI: 10.7937/K9/TCIA.2017.KLXWJJ1Q"},{"@type":"CreativeWork","@id":"https://doi.org/10.7937/K9/TCIA.2017.GJQ7R0EF","name":"S. Bakas, H. Akbari, A. Sotiras, M. Bilello, M. Rozycki, J. Kirby, et al., Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-LGG collection, The Cancer Imaging Archive, 2017. DOI: 10.7937/K9/TCIA.2017.GJQ7R0EF"},{"@type":"CreativeWork","@id":"https://doi.org/10.1038/s41597-024-03073-x","name":"Usman Akbar, M., Larsson, M., Blystad, I., Eklund, A., Brain tumor segmentation using synthetic MR images - A comparison of GANs and diffusion models. Sci Data 11, 259 (2024)."}]},
    "other": {"shortName":"BRGANDI","origin":"Synthetic","status":"Completed","annotation":"The tumor annotation image for each 4-channel MR image was generated by each generative model.\n","countries-shared":["AE","CA","DE","GB","IN","IT","NL","NO","PK","SA","SE","TR","US"],"organ":[{"name":"Brain","sctid":12738006}],"age-span":"","bytes":71924000000,"numberOfScans":"100000 4-channel MR images per generative model","numberOfAnnotations":1000000,"resolution":"1 x 1 x 1 mm","modality":["MR"],"scanner":null,"stain":null,"phase":null,"image":null,"exampleImage":[{"title":"Example image","url":"/assets/images/10.23698/aida/brgandi/image1.png","thumbnail-url":"/assets/images/10.23698/aida/brgandi/image1-thumbnail.png"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n\n<p>Free for use in research or education. Please contact AIDA for terms of access.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/synthetic/brgandi\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2023\nLinköping University, Muhammad Usman Akbar, Linköping University, Anders Eklund</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the purpose\nof medical diagnostics research with or without fee is hereby granted, provided that\nthe above copyright notice and this permission notice appear in all copies, and that\npublications resulting from the use of this data cite the following works:</p>\n\n<p>Muhammad Usman Akbar and Anders Eklund\n(2023)\nSynthetic brain tumor images from GANs and diffusion models\n<a href=\"https://doi.org/10.23698/aida/synthetic/brgandi\">doi:10.23698/aida/synthetic/brgandi</a>.</p>\n\n<p><a href=\"https://doi.org/10.48550/arXiv.2107.02314\">U.Baid, et al., The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification, arXiv:2107.02314, 2021.</a></p>\n\n<p><a href=\"https://doi.org/10.1109/tmi.2014.2377694\">B. H. Menze, A. Jakab, S. Bauer, J. Kalpathy-Cramer, K. Farahani, J. Kirby, et al., The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS), IEEE Transactions on Medical Imaging 34(10), 1993-2024 (2015) DOI: 10.1109/TMI.2014.2377694</a></p>\n\n<p><a href=\"https://doi.org/10.1038/sdata.2017.117\">S. Bakas, H. Akbari, A. Sotiras, M. Bilello, M. Rozycki, J.S. Kirby, et al., Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features, Nature Scientific Data, 4:170117 (2017) DOI: 10.1038/sdata.2017.117</a></p>\n\n<p><a href=\"https://doi.org/10.7937/K9/TCIA.2017.KLXWJJ1Q\">S. Bakas, H. Akbari, A. Sotiras, M. Bilello, M. Rozycki, J. Kirby, et al., Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-GBM collection, The Cancer Imaging Archive, 2017. DOI: 10.7937/K9/TCIA.2017.KLXWJJ1Q</a></p>\n\n<p><a href=\"https://doi.org/10.7937/K9/TCIA.2017.GJQ7R0EF\">S. Bakas, H. Akbari, A. Sotiras, M. Bilello, M. Rozycki, J. Kirby, et al., Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-LGG collection, The Cancer Imaging Archive, 2017. DOI: 10.7937/K9/TCIA.2017.GJQ7R0EF</a></p>\n\n<p><a href=\"https://doi.org/10.1038/s41597-024-03073-x\">Usman Akbar, M., Larsson, M., Blystad, I., Eklund, A., Brain tumor segmentation using synthetic MR images - A comparison of GANs and diffusion models. Sci Data 11, 259 (2024).</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  },

  {
    "datacite": {"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.23698/aida/synthetic/shbamri","name":"Synthetic healthy brain aging MRIs with segmentation masks","about":"Radiology","url":"https://datahub.aida.scilifelab.se/10.23698/aida/synthetic/shbamri","author":[{"name":"Jingru Fu","@id":"https://orcid.org/0000-0003-4175-395X","@type":"Person"},{"name":"Antonios Tzortzakakis","@id":"https://orcid.org/0000-0001-7563-732X","@type":"Person"},{"name":"José Barroso","@type":"Person"},{"name":"Eric Westman","@id":"https://orcid.org/0000-0002-3115-2977","@type":"Person"},{"name":"Daniel Ferreira","@id":"https://orcid.org/0000-0001-9522-4338","@type":"Person"},{"name":"Rodrigo Moreno","@id":"https://orcid.org/0000-0001-5765-2964","@type":"Person"}],"publisher":{"@type":"Organization","name":"AIDA"},"copyrightYear":2023,"copyrightHolder":[{"name":"KTH","url":"https://www.kth.se/","@type":"Organization"},{"name":"Jingru Fu","@id":"https://orcid.org/0000-0003-4175-395X","@type":"Person"},{"name":"KTH","url":"https://www.kth.se/","@type":"Organization"},{"name":"Rodrigo Moreno","@id":"https://orcid.org/0000-0001-5765-2964","@type":"Person"}],"provider":[{"name":"Jingru Fu","email":"jingruf@kth.se","@id":"https://orcid.org/0000-0003-4175-395X","@type":"Person"},{"name":"Rodrigo Moreno","email":"rodmore@kth.se","@id":"https://orcid.org/0000-0001-5765-2964","@type":"Person"},{"name":"Daniel Ferreira","email":"daniel.ferreira.padilla@ki.se","@id":"https://orcid.org/0000-0001-9522-4338","@type":"Person"},{"name":"AIDA Data Hub","email":"aida-data@nbis.se","@id":"https://datahub.aida.scilifelab.se","@type":"Organization"}],"dateCreated":"2023-12-01","datePublished":"2023-12-01","dateModified":"2023-12-01","keywords":"Radiology, Annotated, Brain, MRI, Synthetic, Brain aging, Synthetic brain aging, Medical image generation","version":"1.0.0","description":"This dataset is a collection that includes the 6448 synthetic aging brain T1 MRI scans derived from two data sets by our proposed methodology (the following paper [[1]](https://datahub.aida.scilifelab.se/10.23698/aida/synthetic/shbamri#references)). We augmented the HEALTHY longitudinal brain MRI data with corresponding segmentations to simulate the access of a scan per subject every 6 months in these cohorts.\n","license":[{"name":"Controlled access","id":"https://datahub.aida.scilifelab.se/10.23698/aida/synthetic/shbamri#controlled-access","@type":"CreativeWork","abstract":"Free for use in legal and ethical medical diagnostics research and education.\n"},{"name":"AIDA BY license","id":"https://datahub.aida.scilifelab.se/10.23698/aida/synthetic/shbamri#aida-by-license","@type":"CreativeWork","abstract":"Free for use within AIDA with attribution."}],"citation":[{"@type":"CreativeWork","@id":"https://doi.org/10.1002/hbm.26165","name":"Fast 3D image generation for healthy brain aging using diffeomorphic registration. Fu, Jingru and Tzortzakakis, Antonios and Barroso, José and Westman, Eric and Ferreira, Daniel and Moreno, Rodrigo and for the Alzheimer's Disease Neuroimaging Initiative, 2022. doi: 10.1002/hbm.26165"},{"@type":"CreativeWork","@id":"https://doi.org/10.1101/2019.12.13.19014902","name":"OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer Disease. Pamela J LaMontagne, Tammie L.S. Benzinger, John C. Morris, Sarah Keefe, Russ Hornbeck, Chengjie Xiong, Elizabeth Grant, Jason Hassenstab, Krista Moulder, Andrei Vlassenko, Marcus E. Raichle, Carlos Cruchaga, Daniel Marcus, 2019. medRxiv. doi: 10.1101/2019.12.13.19014902"},{"@type":"CreativeWork","@id":"https://doi.org/10.1002/jmri.21049","name":"The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods. Jack Jr C R, Bernstein M A, Fox N C, et al. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine, 2008, 27(4): 685-691."},{"@type":"CreativeWork","@id":"https://doi.org/10.3389/fninf.2013.00049","name":"Muehlboeck J S, Westman E, Simmons A. TheHiveDB image data management and analysis framework[J]. Frontiers in neuroinformatics, 2014, 7: 49. doi: 10.3389/fninf.2013.00049"}]},
    "other": {"shortName":"SHBAMRI","origin":"Synthetic","status":"Completed","annotation":"All original segmentations were collected by using FreeSurfer (aparc+aseg.mgz). Synthetic images are segmented based on ground truth segmentations using registration, more information can be found in [[1]](https://datahub.aida.scilifelab.se/10.23698/aida/synthetic/shbamri#references).\n","countries-shared":["CN","SE"],"organ":[{"name":"Brain","sctid":12738006}],"age-span":"","bytes":52400000000,"numberOfScans":6448,"numberOfAnnotations":6448,"resolution":"160x160x192, 1X1X1 mm","modality":["MR"],"scanner":null,"stain":null,"phase":null,"image":null,"exampleImage":[{"title":"Sample images and the corresponding segmentation masks.","url":"/assets/images/10.23698/aida/shbamri/SHBAMRI-1-SampleImagesMasks.png","thumbnail-url":"/assets/images/10.23698/aida/shbamri/SHBAMRI-1-SampleImagesMasks-thumbnail.png"},{"title":"The sample brain aging MRI images for a healthy subject from age 51.7 to age 63.7. (Figure 10 from [1])","url":"/assets/images/10.23698/aida/shbamri/SHBAMRI-2-Img2.jpg","thumbnail-url":"/assets/images/10.23698/aida/shbamri/SHBAMRI-2-Img2-thumbnail.jpg"}]},
    "additional": "<h2 id=\"license\">License</h2>\n<h3 id=\"controlled-access\">Controlled access</h3>\n<p>Free for use in legal and ethical medical diagnostics research and education.</p>\n\n<div style=\"margin-top:30px;margin-bottom:30px\">\n<a class=\"button\" href=\"https://rems.dsp.aida.scilifelab.se/apply-for?resource=https://doi.org/10.23698/aida/synthetic/shbamri\">Apply for access</a>\n</div>\n\n<p><a href=\"https://docs.datahub.aida.scilifelab.se/data/data-sharing-request/\">Help with applying for controlled access.</a></p>\n\n<h3 id=\"aida-by-license\">AIDA BY license</h3>\n<p>Copyright\n2023\nKTH, Jingru Fu, KTH, Rodrigo Moreno</p>\n\n<p>Permission to use, copy, modify, and/or distribute this data within Analytic\nImaging Diagnostics Arena (<a href=\"https://medtech4health.se/aida\">AIDA</a>) for the purpose\nof medical diagnostics research with or without fee is hereby granted, provided that\nthe above copyright notice and this permission notice appear in all copies, and that\npublications resulting from the use of this data cite the following works:</p>\n\n<p>Jingru Fu, Antonios Tzortzakakis, José Barroso, Eric Westman, Daniel Ferreira, and Rodrigo Moreno\n(2023)\nSynthetic healthy brain aging MRIs with segmentation masks\n<a href=\"https://doi.org/10.23698/aida/synthetic/shbamri\">doi:10.23698/aida/synthetic/shbamri</a>.</p>\n\n<p><a href=\"https://doi.org/10.1002/hbm.26165\">Fast 3D image generation for healthy brain aging using diffeomorphic registration. Fu, Jingru and Tzortzakakis, Antonios and Barroso, José and Westman, Eric and Ferreira, Daniel and Moreno, Rodrigo and for the Alzheimer’s Disease Neuroimaging Initiative, 2022. doi: 10.1002/hbm.26165</a></p>\n\n<p><a href=\"https://doi.org/10.1101/2019.12.13.19014902\">OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer Disease. Pamela J LaMontagne, Tammie L.S. Benzinger, John C. Morris, Sarah Keefe, Russ Hornbeck, Chengjie Xiong, Elizabeth Grant, Jason Hassenstab, Krista Moulder, Andrei Vlassenko, Marcus E. Raichle, Carlos Cruchaga, Daniel Marcus, 2019. medRxiv. doi: 10.1101/2019.12.13.19014902</a></p>\n\n<p><a href=\"https://doi.org/10.1002/jmri.21049\">The Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods. Jack Jr C R, Bernstein M A, Fox N C, et al. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine, 2008, 27(4): 685-691.</a></p>\n\n<p><a href=\"https://doi.org/10.3389/fninf.2013.00049\">Muehlboeck J S, Westman E, Simmons A. TheHiveDB image data management and analysis framework[J]. Frontiers in neuroinformatics, 2014, 7: 49. doi: 10.3389/fninf.2013.00049</a></p>\n\n<p>THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD\nTO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN\nNO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR\nCONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA\nOR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS\nACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS\nDATA.</p>\n"
  }

]