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Concept-Enhanced Multi-Scale Cross-Modal Alignment for Medical Visual Representation Learning.
Medical Vision-Language Pre-training (Med VLP) on paired medical images and reports has emerged as a promising direction for learning visual representations. However, current alignment approaches remain insufficient for learning fine-grained pathological details, largely due to the inherent difficulty of tokenizing rep...
MSHA-Net: learning with multiscale hierarchical discriminative attention for few-shot medical segmentation
Few-shot medical image segmentation, which aims to achieve accurate segmentation with limited labeled data, faces challenges including 1) the model’s need for strong generalization ability and 2) simultaneous extraction of global semantics and local boundaries. To address these issues, we propose MSHA-NET, a framework...