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Enhances the Medical SAM (Segment Anything Model) by integrating Physics-Informed Neural Networks (PINNs) using the Eikonal equation to enforce geometric and distance-based constraints on medical image segmentations.
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The project combines a SOTA foundation model (MedSAM) with PINNs, specifically the Eikonal equation, which is a sophisticated approach to boundary regularization and distance-field estimation in medical imaging. However, with zero stars and being only 16 days old, it remains a personal research prototype/reimplementation without any community validation or infrastructure.
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