Automatic Grading of Breast Cancer Whole-Slide Histopathology Images

Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Abstract

Grading of tissue based on microscopic images is a common and challenging task. We propose a new method for grading of wholeslide histology images of invasive breast carcinoma, which is based on mitotic cell detection. The method combines a threshold-based attention mechanism and a deep neural network for mitotic cell detection and grading. Our mitotic cell detector is learned from scratch using object centroids. We achieved competitive results in the recent MICCAI TUPAC16 challenge.

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Copyright information

© Springer-Verlag GmbH Deutschland 2017

Authors and Affiliations

  1. 1.Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision GroupUniversity of Heidelberg, BIOQUANT, IPMB, and DKFZ HeidelbergHeidelbergDeutschland

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