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Benchmarking Intra-Patient 3D Deformable Multimodal Image Registration
Multimodal image registration is a key component of many clinical workflows, yet it remains challenging because corresponding anatomical structures often exhibit substantially different image intensities across modalities. In this work, we present a comprehensive benchmark of intra-patient 3D multimodal deformable registration methods across three datasets covering different anatomical regions and difficulty levels, including both synthetic deformation recovery and real clinical scenarios. We evaluate classical optimization-based approaches and modern learning-based methods, including recent d
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-14T14:47:57.000Z
First collected: 2026-09-20T09:41:04.278Z. This is not the publication date.