Learning to combine decisions from multiple mammography views
Alan Joseph Bekker, Moron Shalhon, Hayit Greenspan, Jacob H. Goldberger · 2015
In this paper we address the problem of differentiating between malignant and benign tumors based on their appearance in the CC and MLO mammography views. We describe a two-step classification method that is based on a view-level decision, implemented by a logistic regression classifier, followed by a stochastic combination of the two view-level indications into a single malignant or benign decision. The EM algorithm is used to find the parameters of the proposed model. Our method was evaluated on a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the effectiveness of optimally combining the decisions based on the two views.