Learning-based mitotic cell detection in histopathological images

  title={Learning-based mitotic cell detection in histopathological images},
  author={Christoph Sommer and Luca Fiaschi and Fred A. Hamprecht and Daniel Gerlich},
  journal={Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012)},
Breast cancer grading of histological tissue samples by visual inspection is the standard clinical practice for the diagnosis and prognosis of cancer development. An important parameter for tumor prognosis is the number of mitotic cells present in histologically stained breast cancer tissue sections. We propose a hierarchical learning workflow for automated mitosis detection in breast cancer. From an initial training set a pixel-wise classifier is learned to segment candidate cells, which are… CONTINUE READING

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Key Quantitative Results

  • Based on the candidate segmentation our approach achieves an area-under Precision-Recall-curve of 70% on an annotated dataset, with good localization accuracy, little parameter tuning and small user effort.


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Publications referenced by this paper.
Showing 1-10 of 16 references

Automatic segmentation of clustered breast cancer cells using watershed and concave vertex graph

2011 International Conference on Communications, Computing and Control Applications (CCCA) • 2011
View 1 Excerpt

Ilastik: Interactive learning and segmentation toolkit

2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro • 2011
View 2 Excerpts

Automatic breast cancer grading of histopathological images

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society • 2008
View 1 Excerpt

Grading nuclear pleomorphism on histological micrographs

2008 19th International Conference on Pattern Recognition • 2008
View 1 Excerpt

Comparison of thresholding methods for breast tumor cell segmentation

Proceedings of 7th International Workshop on Enterprise networking and Computing in Healthcare Industry, 2005. HEALTHCOM 2005. • 2005
View 1 Excerpt

Combining intensity

C. Wählby, I. Sintron, F. Erlandsson, G. Borgefors, E. Bengtsson
edge and shape information for 2d and 3d segmentation of cell nuclei in tissue sections. Journal of Microscopy, 215(1):67–76 • 2004
View 1 Excerpt

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