BI-RADS Classification of Calcification on Mammograms

Calcification is one of the most common and important lesions in mammograms, and a higher BI-RADS category indicates a higher cancer risk. In this paper, we present the first deep learning-based six-class BI-RADS classification for each individual calcification in mammograms. We propose an attention ROI generation strategy to highlight calcification features. Moreover, by incorporating malignancy information, the designed new loss function effectively boosts the performance of the model. We also design a novel evaluation metric for BI-RADS classification, which considers the severity of malignancy. Experimental results have demonstrated the superior classification performance of the proposed approach to the competing methods.