Hot-spot selection and evaluation methods for whole slice images of meningiomas and oligodendrogliomas.

The paper presents a combined method for an automatic hot-spot areas selection based on penalty factor in the whole slide images to support the pathomorphological diagnostic procedure. The studied slides represent the meningiomas and oligodendrogliomas tumor on the basis of the Ki-67/MIB-1 immunohistochemical reaction. It allows determining the tumor proliferation index as well as gives an indication to the medical treatment and prognosis. The combined method based on mathematical morphology, thresholding, texture analysis and classification is proposed and verified. The presented algorithm includes building a specimen map, elimination of hemorrhages from them, two methods for detection of hot-spot fields with respect to an introduced penalty factor. Furthermore, we propose localization concordance measure to evaluation localization of hot spot selection by the algorithms in respect to the expert's results. Thus, the results of the influence of the penalty factor are presented and discussed. It was found that the best results are obtained for 0.2 value of them. They confirm effectiveness of applied approach.