@article{,
title= {CAMELYON17 dataset},
journal= {},
author= {Peter Bandi},
year= {},
url= {https://camelyon17.grand-challenge.org/data},
abstract= {CAMELYON17 challenge dataset. The goal of this challenge is to evaluate new and existing algorithms for automated detection and classification of breast cancer metastases in whole-slide images of histological lymph node sections. The dataset contains 1000 WSIs of 200 artificial patients from 5 different medical center and exhaustive annotations for 10 WSIs from each center. The dataset is a slightly updated version of the one available on GigaScience at https://doi.org/10.1093/gigascience/giy065. The changes are: 1. Generated mask files were added for each annotated WSI and 50 additional WSI without tumor with value 1 for normal tissue, and 2 for tumor areas in the corresponding WSI. 2. The images are shared without zipping them together per patient.},
keywords= {whole-slide image, pathology, histology},
terms= {},
license= {https://creativecommons.org/publicdomain/zero/1.0},
superseded= {}
}