Mitosis detection in breast cancer histopathology images

This page contains resources related to the collaboration between the Universities of Surrey and Sheffield for our submission to the AMIDA 2013 challenge.

Team

• Violet Snell
• Teo de Campos (who was in Sheffield, working in Neil Lawrence's lab while this work was done)
• Josef Kittler
• William Christmas

Publication

The paper below shows the results of all methods submitted to the AMIDA 2013 challenge (including ours):

Mitko Veta, Paul J. van Diest, Stefan M. Willems, Haibo Wang, Anant Madabhushi, Angel Cruz-Roa, Fabio Gonzalez, Anders B. L. Larsen, Jacob S. Vestergaard, Anders B. Dahl, Dan C. Ciresan, Jurgen Schmidhuber, Alessandro Giusti, Luca M. Gambardella, F. Boray Tek, Thomas Walter, Ching-Wei Wang, Satoshi Kondo, Bogdan J. Matuszewski, Frederic Precioso, Violet Snell, Josef Kittler, Teofilo E. de Campos, Adnan M. Khan, Nasir M. Rajpoot, Evdokia Arkoumani, Miangela M. Lacle, Max A. Viergever, Josien P.W. Pluim
Assessment of algorithms for mitosis detection in breast cancer histopathology images
Accepted for publication in Medical Image Analysis, Springer, Elsevier, 2015.
Preprint available as a technical report at arXiv:1411.5825.

Resources

• Slides presented at the AMIDA workshop in ICPR 2013
• Violet Snell's PhD viva slides
• Violet Snell's PhD thesis (coming soon)
• Source code
• Bayesian GPLVM (from the Machine Learning group at Sheffield):
• Titsias and Lawrence's paper, JMLR 2010
• Titsias' talk at AISTATS 2010
• Lawrence's talk
• MatLab implementation
• Python implementation