Building multiple weak segmentors for strong mass segmentation in mammogram

This paper proposes to build multiple segmentations for identifying mass contours for a suspicious mass in a mammogram. In this study, by using various parameter settings of the image enhancement functions, we perform multiple segmentations for each suspicious mass (region of interest (ROI)), and multiple mass contours are generated. Each of such segmentations is called a “weak segmentor”, since there is no single image enhancement which produces the optimal segmentation for all mass images. Then for each image, we select the contour which has the highest overlapping ratio as the final segmentation (i.e., the "strong segmentor"). The results show that the overall success rate (81.22%) of the strong segmentor was higher than that of any single weak segmentor. This indicates that using multiple weak segmentors is an effective method to generate a strong mass segmentation for mammograms.