A generic nuclei detection method for histopathological breast images
Henning Höfener, André Homeyer, Peter Bult, Maschenka C. A. Balkenhol, Jeroen van der Laak, Horst Karl Hahn · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2016
The detection of cell nuclei plays a key role in various histopathological image analysis problems. Considering the high variability of its applications, we propose a novel generic and trainable detection approach. Adaption to specific nuclei detection tasks is done by providing training samples. A trainable deconvolution and classification algorithm is used to generate a probability map indicating the presence of a nucleus. The map is processed by an extended watershed segmentation step to identify the nuclei positions. We have tested our method on data sets with different stains and target nuclear types. We obtained F1-measures between 0.83 and 0.93.