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HPR-SAM outperforms existing methods by effectively capturing complex anatomical representations, achieving state-of-the-art results in medical image segmentation without the need for prompts.
Class imbalance in medical image segmentation is no longer a bottleneck: SCDL learns structured class-conditional feature distributions to segment minority structures with state-of-the-art accuracy.
