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.

Keywords: Radiology, Annotated, MR-Linac, Radiotherapy, Prostate, Low-resolution.

Sample images

Sample images with reduced image quality. Please click to preview.

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Dataset information

Short name	LESSER
Origin	Clinical
Cite as	Samuel Fransson and Robin Strand (2023) Low-resolution prostate MR doi:10.23698/aida/lesser [BibTeX format] @misc{ fransson_2023_lesser, author = { Samuel Fransson and Robin Strand }, title = { Low-resolution prostate MR }, year = 2023, publisher = { AIDA }, doi = { 10.23698/aida/lesser }, howpublished = { Available: AIDA Data Hub }, url = { https://datahub.aida.scilifelab.se/10.23698/aida/lesser } }
Field	Radiology
Organ	Prostate
Age span
Title	Low-resolution prostate MR
Author	Samuel Fransson Robin Strand
Year	2023
DOI	doi:10.23698/aida/lesser
Status	Completed
Version	1.0
Scans	310
Annotations	255
Size	5.69GB
Resolution	Varying
Modality	MR
Scanner	Marlin 1.5 T, Elekta Unity
Stain
Phase
References	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
Copyright	Copyright 2022 Medical Physics Region Uppsala, Alexander Englund, Uppsala University, Robin Strand
Access	Available under the following licenses, described in the License section below. Controlled access Free for use in legal and ethical medical diagnostics research. AIDA BY license Free for use within AIDA with attribution.

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.

License

Controlled access

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To: samuel.fransson@akademiska.se
cc: robin.strand@it.uu.se,alexander.englund@akademiska.se,aida-data@nbis.se
Subject: Requesting access to dataset doi:10.23698/aida/lesser
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Dataset: https://datahub.aida.scilifelab.se/10.23698/aida/lesser

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AIDA BY license

Copyright 2022 Medical Physics Region Uppsala, Alexander Englund, Uppsala University, Robin Strand

Permission to use, copy, modify, and/or distribute this data within Analytic Imaging Diagnostics Arena (AIDA) for the purpose of medical diagnostics research with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies, and that publications resulting from the use of this data cite the following works:

Samuel Fransson and Robin Strand (2023) Low-resolution prostate MR doi:10.23698/aida/lesser.

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

THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS DATA.