BACH: Grand challenge on breast cancer histology images

Author:

Aresta Guilherme,Araújo TeresaORCID,Kwok Scotty,Chennamsetty Sai Saketh,Safwan Mohammed,Alex Varghese,Marami Bahram,Prastawa Marcel,Chan Monica,Donovan Michael,Fernandez Gerardo,Zeineh Jack,Kohl MatthiasORCID,Walz Christoph,Ludwig Florian,Braunewell Stefan,Baust Maximilian,Vu Quoc Dang,To Minh Nguyen Nhat,Kim Eal,Kwak Jin TaeORCID,Galal Sameh,Sanchez-Freire Veronica,Brancati NadiaORCID,Frucci Maria,Riccio Daniel,Wang Yaqi,Sun Lingling,Ma Kaiqiang,Fang Jiannan,Kone IsmaelORCID,Boulmane Lahsen,Campilho Aurélio,Eloy Catarina,Polónia AntónioORCID,Aguiar PauloORCID

Funder

FCT

National Research Foundation of Korea

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference66 articles.

1. Improvedautomated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning;Abràmoff,2016

2. Breast Cancer Facts & Figures 2015-2016;American Cancer Society,2015

3. Classification of breast cancer histology images using convolutional neural networks;Araújo;PLoS One,2017

4. Context-aware learning using transferable features for classification of breast cancer histology images;Awan,2018

5. Stain specific standardization of whole-slide histopathological images;Bejnordi;IEEE Trans. Med. Imaging,2016

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