AI RESEARCH
Fuse4Seg: Image Fusion for Multi-Modal Medical Segmentation via Bi-level Optimization
arXiv CS.CV
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ArXi:2409.10328v3 Announce Type: replace Multi-modal medical image fusion is traditionally optimized for human visual perception, aiming to maximize generic contrast and structural fidelity. However, when these visually pleasing fused images are deployed in automated clinical workflows, this visual-semantic discrepancy causes task-agnostic feature degradation, inadvertently smoothing out critical, high-frequency tumor boundaries.