Abstract: In this paper, we describe research carried out within the framework of the optimization of an image analyzer dedicated to rapid detection of abnormalities of ploidy in human tumors. The system takes as its input microscopic images of dissociated cells which are to be segmented in order to extract cellular objects, calculate shape and texture measures, and identify each category of cell, by means of two classification methods that are compared and discussed: classification based on the Bayes decision rule and classification using neural networks. !12
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