DeepBatch: A hybrid deep learning model for interpretable diagnosis of breast cancer in whole-slide images

作者：

Highlights：

• Deep learning model able to predict a refined segmentation of breast cancer in WSI.

• Cascade of CNNs working together inferring global and local characteristics.

• We provide the diagnosis in an interpretable way through segmentation and heat maps.

• Our model identified suspicious regions not labeled in a public dataset.

摘要

•Deep learning model able to predict a refined segmentation of breast cancer in WSI.•Cascade of CNNs working together inferring global and local characteristics.•We provide the diagnosis in an interpretable way through segmentation and heat maps.•Our model identified suspicious regions not labeled in a public dataset.

论文关键词：Deep learning,Whole-slide image,Convolutional neural network,Interpretable diagnosis,Breast cancer,Histopathological images

论文评审过程：Received 27 October 2020, Revised 16 June 2021, Accepted 8 July 2021, Available online 17 July 2021, Version of Record 4 August 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115586