Technique for preprocessing of digital mammogram

Digital mammogram has emerged as the most popular screening technique for early detection of breast cancer and other abnormalities in human breast tissue. It provides us opportunities to develop algorithms for computer aided detection (CAD). In this paper we have proposed three distinct steps. The initial step involves contrast enhancement by using the contrast limited adaptive histogram equalization (CLAHE) technique. Then define the rectangle to isolate the pectoral muscle from the region of interest (ROI) and finally suppress the pectoral muscle using our proposed modified seeded region growing (SRG) algorithm. The proposed algorithms were extensively applied on all the 322 mammogram images in MIAS database resulting in complete pectoral muscle suppression in most of the images. Our proposed algorithm is compared with other segmentation methods showing superior results in comparison.

► Define rectangle to reduce processing and isolate pectoral muscle.
► Suppression of pectoral muscle using proposed modified SRG algorithm.
► Reduce noise, edge-shadowing effect, accurately detect and suppress the pectoral muscle.
► The mean values for CM and CR are 0.976 and 0.980 respectively.