User-guided segmentation for medical image using belief propagation

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초록

Medical image processing is considered on an important elements and image segmentation is still a challenging area. Recently, researches for the CT or MRI images are in progress to measure the degree of fatty degeneration; and the size of muscle rupture. However, the segmentation of the medical image is not easy because of irregularity of muscle shape, noises of the MRI or CT image and unclear boundary features. In this paper, we propose a segmentation method using the active contour with the belief Propagation to overcome the local energy minima problem occurred on the Snake or active contour method. Moreover, the proposed method detects the optimum boundary using the semi-automatic method with the user-guided model and it increase the user convenience and computational efficiency.

키워드

Active contour method; Active contours; Belief propagation; CT Image; Local energy minima; Medical Image Processing; Medical images; MRI Image; Segmentation methods; Semiautomatic methods; Computational efficiency; Computerized tomography; Consumer electronics; Magnetic resonance imaging; Medical imaging; Muscle; Image segmentation
제목
User-guided segmentation for medical image using belief propagation
저자
Chai, Y.; Park, J.; Kim, T.-Y.
DOI
10.1109/ISCE.2011.5973820
발행일
2011-06
유형
Conference Paper
저널명
Proceedings of the International Symposium on Consumer Electronics, ISCE
페이지
226 ~ 227