Mitosis detection in breast cancer histology images with deep neural networks

Dan C. Cireşan, Alessandro Giusti, Luca M. Gambardella, Jürgen Schmidhuber

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1116 Scopus citations

Abstract

We use deep max-pooling convolutional neural networks to detect mitosis in breast histology images. The networks are trained to classify each pixel in the images, using as context a patch centered on the pixel. Simple postprocessing is then applied to the network output. Our approach won the ICPR 2012 mitosis detection competition, outperforming other contestants by a significant margin. © 2013 Springer-Verlag.
Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages411-418
Number of pages8
DOIs
StatePublished - Oct 24 2013
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2022-09-14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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