Recognition of Subtle Microcalcifications in High-Resolution Mammograms

摘要

In this article we present a new method for recognition of subtle mi-crocalcifications in high-resolution digital mammograms. The identification of suspicious regions in mammogram images is carried out using a method based on the 2D discrete wavelet transform. For classification of regions we use the SVC algorithm. Initially, a number of statistical features of mammogram regions was employed to achieve high classification accuracy. Using a novel clustering technique we performed feature selection and identified 18 highly descriptive features. Our method can achieve sensitivity as high as 0.97 while maintaining specificity above 0.90.