The dataset consists of 101 H&E-stained colon whole slide images (WSI) - 52 abnormal and 49 benign cases. All significant abnormal findings identified are outlined and categorized into 15 types such as hyperplastic polyp, high grade adenocarcinoma and necrosis. Other tissue components such as mucosa, submucosa, as well as the surgical margin are delineated to create a complete histological map. In total, 756 separate annotations have been made to segment the different tissue structures and link them to ontological information.

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

Sample images

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

Dataset information

Short name DRCO
Origin Clinical
Cite as Karin Lindman, Martin Lindvall, Caroline Bivik Stadler, Claes Lundstrom, and Darren Treanor (2019) Colon data from the Visual Sweden project DROID doi:10.23698/aida/drco
Field Pathology
Organ Colon
Age span 22-90 years
Title Colon data from the Visual Sweden project DROID
Author Karin Lindman
Martin Lindvall
Caroline Bivik Stadler
Claes Lundstrom
Darren Treanor
Year 2019
DOI doi:10.23698/aida/drco
Status Completed
Version 1.1.0
Scans 101
Annotations 756
Size 49.23GB
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
References
  1. 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. Accurate annotations were made over the whole tissues. 756 separate annotations were made.

Following abnormal findings were annotated for the malign cases: acute and chronic inflammation, acute inflammation, adenocarcinoma, atrophy, chronic inflammation, diverticula, diverticulitis, dysplasia, edema, fibrosis, granulations tissue, hemorrhage, hyalinization, hyperplasia, hyperplastic polyp, inflammation, lymphoma, mucinous adenocarcinoma, necrosis, serrated adenoma, stasis, tubular adenoma, tubulovillous adenoma and ulceration.

Other areas annotated: abnormal, artifact, cecum, colon, colonic mucous membrane, colonic muscularis propria, colonic submucosa, colonic subserosa, descending colon, ileum, normal, rectum, sigmoid colon and transverse colon.

For the benign cases following areas were annotated: artifact, cecum, colon, colonic mucous membrane, colonic muscularis propria, colonic submucosa, colonic subserosa, descending colon, ileum, normal, rectum, sigmoid colon and transverse colon.

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.

You are invited to send an access request email from your institutional account.

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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, Martin Lindvall, Caroline Bivik Stadler, Claes Lundstrom, and Darren Treanor (2019) Colon data from the Visual Sweden project DROID doi:10.23698/aida/drco.

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.