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 deep learning and foundation models, using complementary metrics: Average Dice similarity coeffici...
| Authors | Matteo Barbieri, Giammarco La Barbera, Juan Pablo De La Plata et al. |
|---|---|
| Primary category | cs.CV |
| Published | 14 September 2026 |
| Last updated at source | 14 September 2026 |
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