A Contour-based Mass Segmentation in Mammograms

This paper presents a novel segmentation method for identifying mass regions in mammograms. This work is a part of an on-going project whose aim is to build a Computer-Aided Diagnosis (CADx) system that classifies suspicious cancer masses in mammograms as benign or malignant. Segmentation of suspicious mass regions is an important pre-processing step to achieve high accuracy results, because the regions of interest (ROI) marked by radiologists are oftentimes imprecise. For each ROI, we first apply an enhancement function to increase the grey-level contrast of the image, then a filter function to reduce noise. Next, for each pixel in the ROI, we compute the energy feature based on the co-occurrence matrix of the pixel. Finally we extract a contour of the mass from the energy feature image using an edge-based segmentation technique. We present some examples of our segmentation method and discuss future work.