Automatic classification of clustered microcalcifications by a multiple expert system

Abstract

Mammography is a not invasive diagnostic technique widely used for early cancer detection in women breast. A significant visual clue of the disease is the presence of clusters of microcalcifications. The automatic recognition of malignant clusters of microcalcifications, which could be very helpful for diagnostic purposes, is a very difficult task because of the small size of the microcalcifications and of the poor quality of the mammographic images. In this paper we propose a novel approach for classifying clusters of microcalcifications, based on a Multiple Expert System; such system aggregates several experts, some of which are devoted to classify the single microcalcifications while others are aimed to classify the cluster considered as a whole. The final output results from the suitable combination of the two groups of experts. The tests performed on a standard database of 40 mammographic images have confirmed the effectiveness of the approach.