Computer-aided diagnosis of cross-institutional mammograms using support vector machines with feature elimination

초록

In the analysis of digital or digitized mammographic images, a requirement is to learn to separate benign calcifications from malignant ones. Such an activity could form part of a computer-aided diagnosis (CAD) tool. We present a CAD study of calcification lesions to demonstrate that CAD of same-institutional mammograms provides significantly higher accuracy compared to that of cross-institutional mammograms. Moreover, using only a subset of the widely used six BI-RADS features together with patient age and subtlety value describing each calcification lesion is shown to increase the accuracy of CAD.

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