ROI Extraction of Digital Mammogram Images using Various Comparative Approaches

In this paper we have proposed three different approaches for extracting the Region Of Interest (ROI) in digital mammogram images. Segmentation of the Region of Interest is the first and crucial step in the analysis of digital mammogram images since the success of any Computer Aided Diagnostic (CADx) system depends greatly on the accuracy of the segmentation of the ROI from the mammogram images. Finding an accurate, robust and efficient ROI segmentation technique still remains a challenging problem in digital mammography analysis. Three different segmentation techniques viz., Otsu‟s N thresholding method, k means clustering, and efficient marker controlled watershed transform are applied on the digital mammogram and their results are compared. The results are compared based on the ROI area extracted from the original mammogram image. From the results obtained Otsu‟s N thresholding and k means clustering methods prove to be promising compared to marker controlled watershed transform.