Frozen DINOv3 features with multi-view MLP probes, entropy-weighted fusion, and spatial regularization achieve 0.895 Dice on Kvasir-SEG, 0.897 on ISIC 2018, and 0.908 on BraTS FLAIR, recovering 98.4% of full-data performance with only five annotated patients.
Medical SAM adapter: Adapting segment anything model for medical image segmentation
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SAMRI fine-tunes only the mask decoder of SAM on 1.1 million MRI slices from 30 datasets to reach mean DSC 0.87 on 47 targets and strong zero-shot performance.
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DINO-MVR: Multi-View Readout of Frozen DINOv3 for Annotation-Efficient Medical Segmentation
Frozen DINOv3 features with multi-view MLP probes, entropy-weighted fusion, and spatial regularization achieve 0.895 Dice on Kvasir-SEG, 0.897 on ISIC 2018, and 0.908 on BraTS FLAIR, recovering 98.4% of full-data performance with only five annotated patients.
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SAMRI: Segment Any MRI
SAMRI fine-tunes only the mask decoder of SAM on 1.1 million MRI slices from 30 datasets to reach mean DSC 0.87 on 47 targets and strong zero-shot performance.