Computer-aided detection system of breast masses on ultrasound images

Abstract

We have investigated Computer-aided detection (CAD) system for breast masses on screening ultrasound (US) images. A lot of methods of Computer-aided detection and diagnosis system on US images have been developed by many researchers in the world. However, some methods require substantial computation time in analysing a US image, and some systems also need a radiologist to indicate the masses in advance. In this paper, we proposed fast automatic detection system which utilizes edge information in detecting masses. Our method consists of the following steps: (1) noise reduction and image normalization, (2) decision of the region of interest (ROI) using vertical edges detected by the canny edge detector, (3) segmentation of ROI using watershed algorithm, and (4) reduction of false positives. This study employs 11 whole breast cases with a total of 924 images. All the cases have been diagnosed by a radiologist prior to the study. This database have 11 malignant masses. These malignant masses have heterogeneous internal echo, a low or equal echo-level, and a deficient or disappearance posterior echo. Using the proposed method, the sensitivity in detecting malignant masses is 90.9% (10/11) and the number of false positives per image is 0.69 (633/924). It is concluded that our method is effective for detecting breast masses on US images.