Investigating the performance of a CADx scheme for mammography in specific BIRADS categories

A Computer Aided Diagnosis (CAD_x) pipeline has already been introduced to discriminate between benign and malignant clusters of microcalcifications (MCs). In this study, we evaluate the specific methodologies using cases from publicly available databases of mammograms, the MIAS database and the Digital Database of Screening Mammography (DDSM). Specifically, we investigate various subsets of regions of interest (ROIs) containing cluster of MCs, following the BIRADS assessment performed by radiologists who have participated in the preparation of the databases. The obtained results indicate that there are specific BIRADS categories where the proposed system provides high classification results. Furthermore, it seems that the best results are achieved in obscure cases, where the radiologists have doubts about their diagnosis and recommend extra medical examinations and short follow-up. The reported results indicate the potential of the proposed CAD_x system to assist the diagnostic task of radiologists by providing a reliable second opinion concerning the diagnosis of a cluster of MCs.