ShapeFuse uses bidirectional cross-modal temporal attention and adaptive gating to fuse deformable shape and texture features for cardiac video classification, outperforming existing fusion strategies on a cine CMR dataset.
Medical image analysis 1(1), 35–51 (1996)
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Search-MIND delivers a training-free coarse-to-fine optimization pipeline for multi-modal medical image registration using variance-weighted mutual information and broadened structural descriptors that outperforms ANTs and DINO-reg on liver and abdominal datasets.
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Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification
ShapeFuse uses bidirectional cross-modal temporal attention and adaptive gating to fuse deformable shape and texture features for cardiac video classification, outperforming existing fusion strategies on a cine CMR dataset.
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Search-MIND: Training-Free Multi-Modal Medical Image Registration
Search-MIND delivers a training-free coarse-to-fine optimization pipeline for multi-modal medical image registration using variance-weighted mutual information and broadened structural descriptors that outperforms ANTs and DINO-reg on liver and abdominal datasets.