International Conference on Medical Image Computing and Computer-Assisted Intervention

MICCAI 2014: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 pp 228-235 | Cite as

Empowering Multiple Instance Histopathology Cancer Diagnosis by Cell Graphs

  • Melih Kandemir
  • Chong Zhang
  • Fred A. Hamprecht
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8674)

Abstract

We introduce a probabilistic classifier that combines multiple instance learning and relational learning. While multiple instance learning allows automated cancer diagnosis from only image-level annotations, relational learning allows exploiting changes in cell formations due to cancer. Our method extends Gaussian process multiple instance learning with a relational likelihood that brings improved diagnostic performance on two tissue microarray data sets (breast and Barrett’s cancer) when similarity of cell layouts in different tissue regions is used as relational side information.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Melih Kandemir
    • 1
  • Chong Zhang
    • 2
  • Fred A. Hamprecht
    • 1
  1. 1.Heidelberg University HCI/IWRGermany
  2. 2.CellNetworksHeidelberg UniversityGermany

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