This dataset consists of 174 WSI ovary whole slide images (WSI): 158 malignant and 16 benign. Eight of the most common, histological definable tumour types were annotated: high grade serous carcinoma (HGSC), low grade serous carcinoma (LGSC), clear cell carcinoma (CC), endometrioid adenocarcinoma (EN), metastastic serous carcinoma (MS), metastatic other (MO), serous borderline tumor (SB) and mucinous borderline tumor (MB). Also normal ovarian tissue were annotated. 2402 separate annotations were made. For the benign structures only the epithelial structures, stroma and support tissue were annotated.

Keywords: Pathology, Ovary, Cancer, Whole slide imaging, Annotated.

Sample images

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

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Dataset information

Short name	DROV
Origin	Clinical
Cite as	Karin Lindman, Jerónimo F. Rose, Martin Lindvall, and Caroline Bivik Stadler (2019) Ovary data from the Visual Sweden project DROID doi:10.23698/aida/drov [BibTeX format] @misc{ lindman_2019_drov, author = { Karin Lindman and Jerónimo F. Rose and Martin Lindvall and Caroline Bivik Stadler }, title = { Ovary data from the Visual Sweden project DROID }, year = 2019, publisher = { AIDA }, doi = { 10.23698/aida/drov }, howpublished = { Available: AIDA Data Hub }, url = { https://datahub.aida.scilifelab.se/10.23698/aida/drov } }
Field	Pathology
Organ	Ovary
Age span	17-86 years
Title	Ovary data from the Visual Sweden project DROID
Author	Karin Lindman Jerónimo F. Rose Martin Lindvall Caroline Bivik Stadler
Year	2019
DOI	doi:10.23698/aida/drov
Status	Completed
Version	1.1.0
Scans	193
Annotations	2402
Size	108.59GB
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
References	Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training. J Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4
Copyright	Copyright 2019 Linköping University, Claes Lundström
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

One physician was responsible for the manual annotations controlled by a second pathologist.

Eight of the most common, histological definable tumour types were annotated: high grade serous carcinoma (HGSC), low grade serous carcinoma (LGSC), clear cell carcinoma (CC), endometrioid adenocarcinoma (EN), metastastic serous carcinoma (MS), metastatic other (MO), serous borderline tumor (SB) and mucinous borderline tumor (MB). Also normal ovarian tissue was annotated. In total 2402 separate annotations were made. For the benign structures only the epithelial structures, stroma and support tissue were annotated.

File formats

Pixel position scaling

Coordinates given are relative to the image width. To get the correct pixel position, X coordinates (and Y coordinates!) should therefore be multiplied with the image width.

License

Controlled access

Free for use in legal and ethical medical diagnostics research. Please contact the dataset provider for terms of access.

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To: claes.lundstrom@liu.se
cc: Karin.Lindman@regionostergotland.se,caroline.bivik.stadler@liu.se,aida-data@nbis.se
Subject: Requesting access to dataset doi:10.23698/aida/drov
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AIDA BY license

Copyright 2019 Linköping University, Claes Lundström

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:

Karin Lindman, Jerónimo F. Rose, Martin Lindvall, and Caroline Bivik Stadler (2019) Ovary data from the Visual Sweden project DROID doi:10.23698/aida/drov.

Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training. J Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4

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.