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Proceedings Paper

Level set based vertebra segmentation for the evaluation of Ankylosing Spondylitis
Author(s): Sovira Tan; Jianhua Yao; Michael M. Ward M.D.; Lawrence Yao M.D.; Ronald M. Summers M.D.
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Paper Abstract

Ankylosing Spondylitis is a disease of the vertebra where abnormal bone structures (syndesmophytes) grow at intervertebral disk spaces. Because this growth is so slow as to be undetectable on plain radiographs taken over years, it is necessary to resort to computerized techniques to complement qualitative human judgment with precise quantitative measures on 3-D CT images. Very fine segmentation of the vertebral body is required to capture the small structures caused by the pathology. We propose a segmentation algorithm based on a cascade of three level set stages and requiring no training or prior knowledge. First, the noise inside the vertebral body that often blocks the proper evolution of level set surfaces is attenuated by a sigmoid function whose parameters are determined automatically. The 1st level set (geodesic active contour) is designed to roughly segment the interior of the vertebra despite often highly inhomogeneous and even discontinuous boundaries. The result is used as an initial contour for the 2nd level set (Laplacian level set) that closely captures the inner boundary of the cortical bone. The last level set (reversed Laplacian level set) segments the outer boundary of the cortical bone and also corrects small flaws of the previous stage. We carried out extensive tests on 30 vertebrae (5 from each of 6 patients). Two medical experts scored the results at intervertebral disk spaces focusing on end plates and syndesmophytes. Only two minor segmentation errors at vertebral end plates were reported and two syndesmophytes were considered slightly under-segmented.

Paper Details

Date Published: 10 March 2006
PDF: 10 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614407 (10 March 2006); doi: 10.1117/12.652399
Show Author Affiliations
Sovira Tan, National Institutes of Health (United States)
Jianhua Yao, National Institutes of Health (United States)
Michael M. Ward M.D., National Institutes of Health (United States)
Lawrence Yao M.D., National Institutes of Health (United States)
Ronald M. Summers M.D., National Institutes of Health (United States)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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