MRI based hip degeneration grading is difficult, time-intensive and prone to inter-reader variability, aggravated by the lack of a standard hip grading scale. Recent research using deep learning based clinical classification tasks has shown efficiency in knee degenerative changes. In this study, we aim to develop a deep learning based hip degenerative changes classification model (for cartilage lesions, bone marrow edemas and cysts) and evaluate its performance. In addition to that, we develop an AI-assist tool based on model predictions to test on two radiologists to see if the inter-reader agreement increases by using the AI-assist.
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