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Abstract #0129

Deep Learning Pipeline for Automated Identification of Osteoarthritic Degenerative Changes in the Hip

Eugene Ozhinsky1, Radhika Tibrewala1, Rutwik Shah1, Sarah C. Foreman1, Valentina Pedoia1, and Sharmila Majumdar1

1Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States

Manual identification of bone and cartilage abnormalities in MR images can be laborious and time consuming. The goal of this study was to develop a fully automated deep learning pipeline to identify morphological and degenerative changes in patients with hip osteoarthritis (OA). It included an object detection deep convolutional neural network (DCNN) that generated cropped images of the hip joint and a classification DCNN that identified the presence of morphological bone and cartilage changes.

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