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Abstract #3172

A Marker Controlled Active Contour Model for Thigh Muscle Segmentation in MR Images

Weihong Guo1, Michael Judkovich1, Richard Lartey2, Dongxing Xie2, Mingrui Yang2, and Xiaojuan Li2
1Mathematics, Applied Mathematics and Statistics, Case Western Reserve University, Cleveland, OH, United States, 2Biomedical Engineering, Program of Advanced Musculoskeletal Imaging (PAMI), Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States

Thigh muscle morphology and composition quantified from MR images are potential imaging biomarkers for diseases such as osteoarthritis and sarcopenia. MR thigh muscle segmentation is an important step in quantifying both muscle morphology and composition. Unfortunately, the thigh muscle groups are tightly bundled together, making them very hard to segment due to a lack of clear boundaries between different muscles. We proposed a novel geometric flow based semi-automatic scheme to effectively segment them. We combined reproducible kernel Hilbert space edge descriptor and geodesic distance maps from a set of markers and anti-markers to define the force for the geometric flow.

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