A variational method for automatic localization of the most pathological ROI in the knee cartilage

Arish A. Qazi; Erik B. Dam; Marco Loog; Mads Nielsen; Francois Lauze; Claus Christiansen M.D.

doi:10.1117/12.769682

11 March 2008 A variational method for automatic localization of the most pathological ROI in the knee cartilage

Arish A. Qazi, Erik B. Dam, Marco Loog, Mads Nielsen, Francois Lauze, Claus Christiansen M.D.

Author Affiliations +

Proceedings Volume 6914, Medical Imaging 2008: Image Processing; 69140T (2008) https://doi.org/10.1117/12.769682
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Osteoarthritis (OA) is a degenerative joint disease characterized by degradation of the articular cartilage, and is a major cause of disability. At present, there is no cure for OA and currently available treatments are directed towards relief of symptoms. Recently it was shown that cartilage homogeneity visualized by MRI and representing the biochemical changes undergoing in the cartilage is a potential marker for early detection of knee OA. In this paper based on homogeneity we present an automatic technique, embedded in a variational framework, for localization of a region of interest in the knee cartilage that best indicates where the pathology of the disease is dominant. The technique is evaluated on 283 knee MR scans. We show that OA affects certain areas of the cartilage more distinctly, and these are more towards the peripheral region of the cartilage. We propose that this region in the cartilage corresponds anatomically to the area covered by the meniscus in healthy subjects. This finding may provide valuable clues in the pathology and the etiology of OA and thereby may improve treatment efficacy. Moreover our method is generic and may be applied to other organs as well.

Citation Download Citation

Arish A. Qazi, Erik B. Dam, Marco Loog, Mads Nielsen, Francois Lauze, and Claus Christiansen M.D. "A variational method for automatic localization of the most pathological ROI in the knee cartilage", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69140T (11 March 2008); https://doi.org/10.1117/12.769682

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