… the breast cancer image analysis field, the Grand Challenge on BreAst Cancer Histology
images … International Conference on Image Analysis and Recognition) 3 . BACH is a biomedical …

… Moreover, the same approach provided an excellent classification performance with an
accuracy of 88.50% when applied on the ICIAR 2018 grand challenge dataset using 5-fold cross …

… -wise” network performs classification of the whole image. The first network is pre-… image.
We trained the networks using the ICIAR 2018 grand challenge on BreAst Cancer Histology (…

… , for the task of breast histology image classification into four tissue … , benign, in situ carcinoma
and invasive carcinoma. The … grand challenge Footnote 1 , comprising H&E-stained breast …

… 2018 Grand Challenge on BreAst Cancer Histology images (… -class classification of breast
cancer histology images. Here … of multi-class breast cancer histology image classification. Our …

… images provided for the Grand Challenge on Breast Cancer … -classification of breast
cancer histology images based on the … The classification of a breast cancer histology image is …

… breast cancer histology image classification. Hematoxylin and eosin stained breast histology
microscopy image … ICIAR 2018 Grand Challenge on Breast Cancer Histology Images. Our …

… ) organized the Breast Pathology Quantitative Biomarkers (BreastPathQ) Grand Challenge
to … for the determination of cancer cellularity in breast cancer patients treated with NAT from …

… For the breast cancer classification, the cancer types considered in the present work are …
2018 grand challenge. The main motive of this work is to obtain better result for histology image …

… We used a breast cancer dataset provided as part of Camelyon-16 grand challenge. It
contains a total of 400 whole-slide images (WSIs) of sentinel lymph node from two independent …