Gradient Vector Flow Field and Mass Region Extraction in Digital Mammograms

Abstract

Mass detection is one of the main computer-aided mammographic breast cancer detection techniques. Precisely selecting the regions that contain masses is an important step in mass segmentation using mammographic computer-aided detection. In this paper, an algorithm for extracting mass regions in digital mammograms is proposed, in which we use adaptive histogram equalization to enhance mammograms, use a gradient vector flow field to generate region boundaries, select N candidate locations according to the means and the standard deviations of intensities of the points with top brightness, use these points and the region boundaries to generate the convex hulls of the regions as the mass regions. 161 down-sampled mammogram images from the Digital Database for Screening Mammography project were test, and a detection rate of 82.6% is obtained. The experimental results indicated that the method is efficient and robust.