Detection of masses in mammograms using region growing controlled by multilevel thresholding

Abstract

Mammographic masses are important signs of breast cancer. However, due to its irregular and obscured margin, variability in size, and occlusion within dense breast tissue, a mass is often difficult to detect. In this paper, a multilevel thresholding approach controlled by gradient and intensity is proposed, where an image is considered as a 3D topographic map with intensity as the third dimension. A multilevel high-to-low intensity thresholding approach is used for the detection of the focal region of a mass. After each step of thresholding, a region growing technique is applied on each focal region to detect potential sites of masses using gradient and intensity information. The performance of the proposed method is tested on 107 scanned-film images consisting of 52 images with masses and 55 normal images from the mini-MIAS database, and 158 digital radiography (DR) images containing 78 images with masses and 80 normal images from a local database. A sensitivity of 95% with 5.2 false positives (FPs)/image is obtained with the mini-MIAS images and a sensitivity of 98.8% with 2.1 FPs/image is obtained with the DR images.