Using instance normalization, GIN intensity augmentation, and supervised contrastive loss improves total knee replacement prediction from FS-IW-TSE MRI when tested on DESS MRI.
Discovering knee osteoarthritis imaging features for diagnosis and prognosis: Review of manual imaging grading and machine learning approaches,
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Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction
Using instance normalization, GIN intensity augmentation, and supervised contrastive loss improves total knee replacement prediction from FS-IW-TSE MRI when tested on DESS MRI.