Learning-based mitotic cell detection in histopathological images

@article{Sommer2012LearningbasedMC,
  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)},
  year={2012},
  pages={2306-2309}
}
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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  • 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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