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Proceedings Paper

Cartilage segmentation of 3D MRI scans of the osteoarthritic knee combining user knowledge and active contours
Author(s): John Andrew Lynch; Souhil Zaim; Jenny Zhao; Alexander Stork; Charles G. Peterfy; Harry K. Genant
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Paper Abstract

A technique for segmentation of articular cartilage from 3D MRI scans of the knee has been developed. It overcomes the limitations of the conventionally used region growing techniques, which are prone to inter- and intra-observer variability, and which can require much manual intervention. We describe a hybrid segmentation method combining expert knowledge with directionally oriented Canny filters, cost functions and cubic splines. After manual initialization, the technique utilized 3 cost functions which aided automated detection of cartilage and its boundaries. Using the sign of the edge strength, and the local direction of the boundary, this technique is more reliable than conventional 'snakes,' and the user had little control over smoothness of boundaries. This means that the automatically detected boundary can conform to the true shape of the real boundary, also allowing reliable detection of subtle local lesions on the normally smooth cartilage surface. Manual corrections, with possible re-optimization were sometimes needed. When compared to the conventionally used region growing techniques, this newly described technique measured local cartilage volume with 3 times better reproducibility, and involved two thirds less human interaction. Combined with the use of 3D image registration, the new technique should also permit unbiased segmentation of followup scans by automated initialization from a baseline segmentation of an earlier scan of the same patient.

Paper Details

Date Published: 6 June 2000
PDF: 11 pages
Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387758
Show Author Affiliations
John Andrew Lynch, Univ. of California/San Francisco (United States)
Souhil Zaim, Univ. of California/San Francisco (United States)
Jenny Zhao, Univ. of California/San Francisco (United States)
Alexander Stork, Univ. of California/San Francisco (United States)
Charles G. Peterfy, Univ. of California/San Francisco (United States)
Harry K. Genant, Univ. of California/San Francisco (United States)


Published in SPIE Proceedings Vol. 3979:
Medical Imaging 2000: Image Processing
Kenneth M. Hanson, Editor(s)

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