SGP-Net improves few-shot medical image segmentation by using spectral frequency decomposition for cue disentanglement and geodesic matching on feature manifolds instead of cosine similarity.
Dual contrastive learning with anatomical auxiliary supervision for few-shot medical image segmentation,
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Beyond Euclidean Prototypes: Spectral Disentanglement and Geodesic Matching for Few-Shot Medical Image Segmentation
SGP-Net improves few-shot medical image segmentation by using spectral frequency decomposition for cue disentanglement and geodesic matching on feature manifolds instead of cosine similarity.