Asymmetry Recognition of Mammogram Images Based on Convolutional Neural Network
Yi‐Chong Zeng · 2019
Mammography is the first process to acquire breast imaging data. Approved radiologists screen the mammogram images for detecting suspicious lesions, e.g., mass, calcification, asymmetry. However, image screening is time-consuming and is a subjective decision-making process. In this paper, we propose an asymmetry recognition scheme with various convolutional neural network (CNN) architectures. The proposed scheme not only determines whether a pair of mammogram images is asymmetry, but it indicates that which image asymmetry occurs in.