BI-RADS features-based computer-aided diagnosis of abnormalities in mammographic images

초록

In the analysis of digital or digitized mammographic images, a requirement is to learn to separate benign abnormalities from malignant ones. Such an activity could form part of a computer-aided diagnosis (CAD) tool. We present a CAD study of mass and calcification lesions found in Digital Database of Screening Mammography (DDSM) using BI-RADS-based features to demonstrate the performance of feature elimination-based support vector machines as the classification technique. It is shown that using only a subset of the available set of features is shown to significantly better classify abnormalities. Furthermore, it is also shown that CAD of same-institutional mammogram produces higher classification accuracy in general compared to that of cross-institutional mammograms.

키워드