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.