Detection of Microcalcification in Digitized Mammograms Using Weighted Local Differences and Local Contrast

Breast cancer remains one of the deadliest diseases among women. Microcalcifications can be an early indicator of a breast cancer. Thus when they are present their detection during a screening test is very crucial. But due to their small size and low contrast in mammographies their detection is difficult. Therefore many computer aided diagnosis mathods have been developped to help and assist rediologist during their screening tests. This paper presents a novel approach to detect microcalcifications on digitized mammaographies using fuzzy logic and support vector machines with 9 statistical and geometric features. Our method was tested on 120 cases from the Mias database including 22 microcalcification cases, 60 normal cases and 70 abnormal cases.We have reached an Az Value of 0,91 making this method very comparable to the State Of Art works.