Extraction of neurons from images of mouse brain slices based on automated selection of connected morphological filters

We describe the results of a study on creating an algorithm for automated selection of connected morphological filters to solve image segmentation problems. We propose a similarity measure for image partition. It is used to select the best filters from given families of connected morphological filters in such a way that partition obtained by applying the watershed-segmentation algorithm to a filtered image has the maximum similarity value with the given partition. This method is used to extract neurons from images of mouse brain slices. Experimental research has confirmed that this method is applicable for automated processing and analysis of slice images.