Mammographic mass detection based on extended concentric morphology model
Yanfeng Li, Houjin Chen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2014
Breast cancer occurs with high frequency among women. In most cases, the main early signs appear as mass and calcification. Distinguishing masses from normal tissues is still a challenging work as mass varies with shapes, margins and sizes. In this paper, a novel method for mass detection in mammograms was presented. First, morphology operators are employed to locate mass candidates. Then anisotropic diffusion was applied to make mass region display better multiple concentric layers (MCL). Finally an extended concentric morphology model (ECMM) criterion combining MCL criterion and template matching was proposed to detect masses. This method was examined on 170 images from Digital Database for Screening Mammography (DDSM) database. The detection rate is 93.92% at 1.88 false positives per image (FPs/I), demonstrating the effectiveness of the proposed method.