Mammographic image segmentation using combined morphological filtering and contextual Bayesian labeling

Abstract

The objective of this study is to develop an efficient method to highlight the geometric characteristics of defined patterns, and isolate the suspicious regions which in turn provide the improved segmentation of objects. In this paper, a combined method of using morphological operations and contextual Bayesian relaxation labeling was developed to enhance and segment various mammographic contexts and textures. This method has been used to segment mammographic images for the extraction of masses. The testing results showed that the proposed method can detect all suspected masses as well as high contrast objects.