Parallel Birth and Death Process for Cell Nuclei Extraction in Histopathology Images

Cell nuclei extraction from histopathology images is necessary for breast cancer grading, and has become one of the major problem in the domain of automatic image analysis. Stochastic marked point processes combined with birth and death processes are promising tools for such extraction, but they are extremely compute intensive, especially on large images such as scanned microscope slides. We here show that the original birth and death process applied to marked point processes is inherently sequential. We thus rewrite this algorithm in order to obtain a highly parallel birth and death process. This algorithm is finally efficiently deployed on multi-core and many-core architectures, and the corresponding performance results are presented and analyzed.