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Abstract #5105

Semi-automated Segmentation of Hip Cartilage in Physiological Magnetic Resonance Imaging: A Fast, Accurate, and Clinically Viable Methodology

Daniel J Park1, Scott Fernquest1, Antony Palmer1, Marija Marcan2, Irina Voiculescu2, and SiƓn Glyn-Jones1

1Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom, 2Department of Computer Science, University of Oxford, Oxford, United Kingdom

Physiological Magnetic Resonance imaging (pMRI) offers the potential of diagnosing osteoarthritis at a stage where patients may benefit from intervention, and acting as an assay of disease to test the efficacy of novel early intervention treatments. pMRI data, however, requires segmentation to allow morphological and biochemical quantitative analysis. Manual segmentation is time consuming and a viable automated segmentation method in the hip remains elusive. We have produced a fast, accurate, and reproducible semi-automated method of segmentation to allow wider implementation of pMRI for use in quantitative analysis of early OA in the hip in both research and clinical settings.

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