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Classifying clusters of microcalcifications in digitized mammograms by bayesian network

The purpose of this work is the evaluation and analysis of bayesian network models in order to classify clusters of microcalcification to supply a second opinion to the specialists in the detection of breast diseases by mammography. From regions of interest (ROI) containing clusters of microcalcifications, features based on the moments theory were extracted and used as the input to a bayesian network. By using a free software of bayesian network models constriction, some tests were performed in order to build the classifier. The first results of validation have shown 83.17% of correct results.