Artificial intelligence (AI) can provide significant utility in the management of hip disorders by analyzing MR images. AI can automate image segmentation with success. Current models have been successfully tested in the diagnosis of osteoarthritis, femoroacetabular impingement, labral tears, developmental dysplasia of the hip, infection, osteonecrosis of the femoral head, and bone tumors. Many of these models have shown strong performances with accuracies in the range of 76% to 97%, and area under the curve of 77% to 98%. The recent trends indicate high interest and adoption of these tools in MR imaging assessment of hip disorders.
Keywords: Artificial intelligence; Deep learning; Hip; Hip imaging; MR Imaging; Machine learning; Magnetic resonance.
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