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 with reduced image quality. Please click to preview.
|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|
|Age span||17-86 years|
|Title||Ovary data from the Visual Sweden project DROID|
Jerónimo F. Rose
Caroline Bivik Stadler
|Resolution||20X single plane|
Scanscope AT (Aperio, US)
NanoZoomer XR (Hamamatsu, Japan)
NanoZoomer XRL (Hamamatsu, Japan)
|Stain||H&E (hematoxylin and eosin)|
|Copyright||Copyright 2019 Linköping University, Claes Lundström|
Available under the following licenses, described in the License section below.
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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.
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.
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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
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