Abstract #4803

Machine Learning-based Human Knee Cartilage Segmentation on MRI

Siddhi Munde¹, Melissa N Manzer¹, Wellsandt Elizabeth², Jessica Emory³, and Balasrinivasa R Sajja¹

¹Radiology, University of Nebraska Medical Center, Omaha, NE, United States, ²Division of Physical Therapy, University of Nebraska Medical Center, Omaha, NE, United States, ³University of Nebraska Medical Center, Omaha, NE, United States

Accurate knee cartilage segmentation on MRI is essential to obtain quantitative measures from cartilage that help in the assessment of knee pathology and therapeutic response in patients with diseases such as Osteoarthritis. Segmentation of cartilage on routine clinical MRI is challenging due to image intensity variation across the structure and low image contrast. In this study, we obtained an accurate cartilage segmentation on PD and T1 weighted images using Support Vector Machine (SVM) classifier with a spatial indexing feature which accounts for regional signal variations.

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