Automatic lesion detection and segmentation algorithm on 2D breast ultrasound images
Donghoon Yu, Sooyeul Lee, Jeong Won Lee, Seung-Hwan Kim · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Although X-ray mammography (MG) is the dominant imaging modality, ultrasonography (US), with recent advances in technologies, has proven very useful in the evaluation of breast abnormalities. But radiologist should investigate a lot of images for proper diagnosis unlike MG. This paper proposes the automatic algorithm of detecting and segmenting lesions on 2D breast ultrasound images to help radiologist. The detecting part is based on the Hough transform with downsampling process which is very efficient to sharpen the smooth lesion boundary and also to reduce the noise. In segmenting part, radial dependent contrast adjustment (RDCA) method is newly proposed. RDCA is introduced to overcome the limitation of Gaussian constraint function. It decreases contrast around the center of lesion but increases contrast proportional to the distance from the center of lesion. As a result, segmentation algorithm shows robustness in various shapes of lesion. The proposed algorithms may help to detect lesions and to find boundary of lesions efficiently.