i3S Annotated Datasets on Digital Pathology WELCOME In an effort to contribute and push forward the field of Digital Pathology, Ipatimup and INEB, two major research institutions in Portugal, have joined forces in the construction of histology datasets to support grand Challenges on automatic classification of tissue malignancy. The researchers/pathologists responsible for the datasets are: António Polónia (MD), Ipatimup/i3S Catarina Eloy (MD, PhD), Ipatimup/i3S Paulo Aguiar (PhD), INEB/i3S This specific page refers to the Grand Challenge on Breast Cancer Histology images, or BACH Challenge THE BACH CHALLENGE DATASET ICIAR 2018 - Grand Challenge on Breast Cancer Histology images [Challenge organized by Teresa Araújo, Guilherme Aresta, António Polónia, Catarina Eloy and Paulo Aguiar] For detailed information visit: https://iciar2018-challenge.grand-challenge.org/home/ THIS DATASET IS PUBLICALLY AVAILABLE UNDER A CREATIVE COMMONS CC BY-NC-ND LICENSE (ATTRIBUTION-NONCOMMERCIAL-NODERIVS) ESSENCIALLY, YOU ARE GRANTED ACCESS TO THE DATASET FOR USE IN YOUR RESEARCH AS LONG AS YOU CREDIT OUR WORK/PUBLICATIONS(*), BUT YOU CANNOT CHANGE THEM IN ANY WAY OR USE THEM COMMERCIALLY (*) Aresta, Guilherme, et al. "BACH: Grand challenge on breast cancer histology images." Medical image analysis (2019). (*) Araújo, Teresa, et al. "Classification of breast cancer histology images using convolutional neural networks." PloS one 12.6 (2017): e0177544. (*) Fondón, Irene, et al. "Automatic classification of tissue malignancy for breast carcinoma diagnosis." Computers in biology and medicine 96 (2018): 41-51.