Abstract
Purpose: To evaluate the performance of 8 state-of-the-art knee MRI segmentations methods for assessment of cartilage quantity changes in clinical trials.While deep learning (DL) methods have demonstrated impressive, near-human performance for many image analysis tasks, some of the methods have been shown to be sensitive to changes in data distributions. For a multi-center, longitudinal study, there will be distribution shifts between centers and over time due to scanner software (e.g. image reconstruction methods) and hardware upgrades (coils, gradients, etc.).
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