MSR:Hybrid Field Modeling for CT-MRI Rigid-Deformable Registration of the Cervical Spine with an Annotated Dataset
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Abstract (arXiv)
Accurate CT-MRI registration of the cervical spine is essential for preoperative planning because this region is anatomically complex,highly variable,and vulnerable to injury of the vertebral arteries and spinal cord. However,cervical CT-MRI registration remains underexplored,particularly for rigid-deformable hybrid modeling,and the lack of high-quality annotated multimodal data further limits progress. To address these challenges, we construct and release a comprehensively annotated CT-MRI dataset, R-D-Reg, and propose MSR, a rigid-deformable hybrid registration framework for complex joint structures. Specifically, MSR includes a rigid registration module for independent local rigid alignment of individual vertebrae and a deformable registration module with an MSL block that combines Mamba-based global modeling and Swin Transformer-based local modeling through adaptive gating. The rigid and deformable deformation fields are then fused to generate a hybrid field that better preserves local anatomical consistency. The code and dataset are publicly available at https://github.com/ssc1230609-spec/MSR-registration.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 33 references that are in the map. First posted on arXiv 30 Apr 2026.
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References · 8
- 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
- 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,718
- 2021Efficiently Modeling Long Sequences with Structured State Spacescited by 2,465
- 2018VoxelMorph: A Learning Framework for Deformable Medical Image Registrationcited by 662
- 2022TotalSegmentator: robust segmentation of 104 anatomical structures in CT imagescited by 613
- 2024MambaVision: A Hybrid Mamba-Transformer Vision Backbonecited by 224
- 2025SynthRAD2025 Grand Challenge dataset: generating synthetic CTs for radiotherapycited by 28
- 2022Weakly-supervised Biomechanically-constrained CT/MRI Registration of the Spinecited by 6
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- 2024MambaMorph: a Mamba-based Framework for Medical MR-CT Deformable Registration
- 2025MM2CT: MR-to-CT translation for multi-modal image fusion with mamba
- 2024SpineMamba: Enhancing 3D Spinal Segmentation in Clinical Imaging through Residual Visual Mamba Layers and Shape Priors
- 2023Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation
- 2024MedDet: Generative Adversarial Distillation for Efficient Cervical Disc Herniation Detection
- 2025Expert Validation of Synthetic Cervical Spine Radiographs Generated with a Denoising Diffusion Probabilistic Model
- 2024VMambaMorph: a Multi-Modality Deformable Image Registration Framework based on Visual State Space Model with Cross-Scan Module
- 2026Topology-Guided Biomechanical Profiling: A White-Box Framework for Opportunistic Screening of Spinal Instability on Routine CT