Mitosis detection in breast cancer histology images with deep neural networks

Med Image Comput Comput Assist Interv. 2013;16(Pt 2):411-8. doi: 10.1007/978-3-642-40763-5_51.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Biopsy
  • Breast Neoplasms / pathology*
  • Breast Neoplasms / physiopathology*
  • Cell Nucleus / pathology*
  • Female
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods
  • Microscopy / methods*
  • Mitosis*
  • Neural Networks, Computer*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity