Pectoral Muscle Segmentation in Mammograms Based on Anatomic Features

Abstract

In this paper, an anatomic features-based method is proposed to segment the pectoral muscle region according to texture feature and shape feature. Firstly, spectral clustering combined with edge information is presented and used to segment the pectoral muscle, leading to an over-segmented result. Afterwards, a region merging algorithm is proposed on the basis of the intensity distribution of regions and the characteristic of triangle shape. Finally, the pectoral muscle is identified from the over-segmented result according to region merging. The proposed method is evaluated on 322 mammograms from the mammographic image analysis society (mini-MIAS) database and 50 mammograms from the Breast Center of Peking University People s Hospital (BCPKUPH). The results show that the proposed method works well for pectoral muscles of different sizes, shapes and intensities.