动态血管建模框架，实现手术模拟中实时精准的冠状动脉变形。
Time-Varying Coronary Artery Deformation: A Dynamic Skinning Framework for Surgical Training
- 基于双调和能量最小化计算骨骼权重，结合四面体网格实现动态变形。
- 平均霍夫德距离4.96mm，表面距离1.78mm，分支完整度与连续性表现优异。
- 适合虚拟手术训练，支持导丝碰撞检测与造影剂流动模拟。
目的：提出一种新型解剖驱动的动态建模框架，利用骨骼蒙皮权重计算实现冠状动脉的精确变形控制，同时保持手术模拟所需的实时性能。方法：基于双调和能量最小化构建计算框架，通过四面体网格进行体积离散化，采用时间采样与插值实现心脏周期内连续的血管变形，引入机械约束与体积守恒。在5例临床数据上验证，将插值结果与逐帧分割得到的真实数据对比。结果：该框架有效支持交互式血管操作；几何精度评估显示，插值网格与真实模型间平均霍夫德距离为4.96 ± 1.78 mm，平均表面距离为1.78 ± 0.75 mm；分支完整度比为1.82 ± 0.46，分支连续性评分维持在0.84 ± 0.06（0-1量表）。系统具备实时导丝-血管碰撞检测与全冠脉结构下造影剂流动模拟能力。结论：基于蒙皮权重的方法提升了模型的交互性与适用性，同时保持高几何精度，为虚拟手术训练系统提供更灵活的技术基础，在临床实践与医学教育中具有应用前景。代码已开源：https://github.com/ipoirot/DynamicArtery。
原文摘要 · Abstract (English)
Purpose: This study proposes a novel anatomically-driven dynamic modeling framework for coronary arteries using skeletal skinning weights computation, aiming to achieve precise control over vessel deformation while maintaining real-time performance for surgical simulation applications. Methods: We developed a computational framework based on biharmonic energy minimization for skinning weight calculation, incorporating volumetric discretization through tetrahedral mesh generation. The method implements temporal sampling and interpolation for continuous vessel deformation throughout the cardiac cycle, with mechanical constraints and volume conservation enforcement. The framework was validated using clinical datasets from 5 patients, comparing interpolated deformation results against ground truth data obtained from frame-by-frame segmentation across cardiac phases. Results: The proposed framework effectively handled interactive vessel manipulation. Geometric accuracy evaluation showed mean Hausdorff distance of 4.96 +- 1.78 mm and mean surface distance of 1.78 +- 0.75 mm between interpolated meshes and ground truth models. The Branch Completeness Ratio achieved 1.82 +- 0.46, while Branch Continuity Score maintained 0.84 +- 0.06 (scale 0-1) across all datasets. The system demonstrated capability in supporting real-time guidewire-vessel collision detection and contrast medium flow simulation throughout the complete coronary tree structure. Conclusion: Our skinning weight-based methodology enhances model interactivity and applicability while maintaining geometric accuracy. The framework provides a more flexible technical foundation for virtual surgical training systems, demonstrating promising potential for both clinical practice and medical education applications. The code is available at https://github.com/ipoirot/DynamicArtery.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。