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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