- Created by natasha honomichl on Apr 26, 2019
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Summary
This data was used for the BreastPathQ challenge co-sponsored by SPIE/AAPM/NCI and currently 338 participants have registered on the CodaLab site to download patches from these WSIs. The aim of the data collection ws to train and validate methods of assessing residual tumour cellularity after NAT. We also have annotations for malignant and benign epithelial cells and TILs which are valuable for assessing performance of cell classification methods. This collection is distinct from other collections as it is focused on post-NAT patients with residual tumour and was collected to allow automatic methods of residual cancer burden to be developed. There are many histopathological changes that occur after therapy and the image data is linked with information about receptor status and treatment type making this a unique resource.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
- Funding from the Canadian Cancer Society, grant #705772 National Cancer institute of the National Institutes of Health under #U24CA199374
Data Access
Click the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever. Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.
Data Type | Download all or Query/Filter |
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Images (SVS, XX.X GB) |
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Supplemental Data (XML) |
Click the Versions tab for more info about data releases.
Detailed Description
Image Statistics | |
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Modalities | Pathology |
Number of Patients | 64 |
Number of Studies | |
Number of Series | |
Number of Images | 96 |
Images Size (GB) |
Citations & Data Usage Policy
Add any special restrictions in here.
These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work:
Data Citation
DOI goes here. Create using pubhub with information from Collection Approval form
Publication Citation
1) Peikari, M., Salama, S., Nofech-Mozes, S. and Martel, A.L., 2017. Automatic cellularity assessment from post-treated breast surgical specimens. Cytometry Part A, 91(11), pp.1078-1087.
TCIA Citation
Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7
Other Publications Using This Data
TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.
Version 1 (Current): Updated 2019/04/26
Data Type | Download all or Query/Filter |
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Images (SVS) | (Requires NBIA Data Retriever.) |
Clinical Data (CSV) | Link |
Other (XML) |
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