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Proceedings Paper

Automatic bone segmentation in knee MR images using a coarse-to-fine strategy
Author(s): Sang Hyun Park; Soochahn Lee; Il Dong Yun; Sang Uk Lee
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Paper Abstract

Segmentation of bone and cartilage from a three dimensional knee magnetic resonance (MR) image is a crucial element in monitoring and understanding of development and progress of osteoarthritis. Until now, various segmentation methods have been proposed to separate the bone from other tissues, but it still remains challenging problem due to different modality of MR images, low contrast between bone and tissues, and shape irregularity. In this paper, we present a new fully-automatic segmentation method of bone compartments using relevant bone atlases from a training set. To find the relevant bone atlases and obtain the segmentation, a coarse-to-fine strategy is proposed. In the coarse step, the best atlas among the training set and an initial segmentation are simultaneously detected using branch and bound tree search. Since the best atlas in the coarse step is not accurately aligned, all atlases from the training set are aligned to the initial segmentation, and the best aligned atlas is selected in the middle step. Finally, in the fine step, segmentation is conducted as adaptively integrating shape of the best aligned atlas and appearance prior based on characteristics of local regions. For experiment, femur and tibia bones of forty test MR images are segmented by the proposed method using sixty training MR images. Experimental results show that a performance of the segmentation and the registration becomes better as going near the fine step, and the proposed method obtain the comparable performance with the state-of-the-art methods.

Paper Details

Date Published: 14 February 2012
PDF: 6 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 831405 (14 February 2012); doi: 10.1117/12.910868
Show Author Affiliations
Sang Hyun Park, Seoul National Univ. (Korea, Republic of)
Soochahn Lee, SAMSUNG Electronics (Korea, Republic of)
Il Dong Yun, Hankuk Univ. of Foreign Studies (Korea, Republic of)
Sang Uk Lee, Seoul National Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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