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Proceedings Paper

Automatic lesion detection and segmentation algorithm on 2D breast ultrasound images
Author(s): Donghoon Yu; Sooyeul Lee; Jeong Won Lee; Seunghwan Kim
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Paper Abstract

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.

Paper Details

Date Published: 8 March 2011
PDF: 6 pages
Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79631Y (8 March 2011); doi: 10.1117/12.876351
Show Author Affiliations
Donghoon Yu, Electronics and Telecommunications Research Institute (Korea, Republic of)
Sooyeul Lee, Electronics and Telecommunications Research Institute (Korea, Republic of)
Jeong Won Lee, Electronics and Telecommunications Research Institute (Korea, Republic of)
Seunghwan Kim, Electronics and Telecommunications Research Institute (Korea, Republic of)


Published in SPIE Proceedings Vol. 7963:
Medical Imaging 2011: Computer-Aided Diagnosis
Ronald M. Summers; Bram van Ginneken, Editor(s)

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