发表机构
Automation Core Inc.（自动化核心公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出基于物理的信念状态世界模型，在稀疏透视下以粒子滤波维持导管导航，验证了校准信念而非点估计精度是稀疏成像导航的关键属性。
AI 中文摘要
血管内导管导航依赖于连续透视，这使患者和临床工作人员在整个手术过程中暴露于电离辐射。我们研究基于物理的世界模型能否在刻意稀疏的X射线采集之间维持导航任务，以及该模型能否在其内部状态估计不再可靠时发出信号。我们将稀疏透视导航表述为部分可观测马尔可夫决策过程，其中Cosserat杆模拟器提供转移动力学，稀疏噪声投影提供观测，粒子滤波器维持对设备状态的信念，在本实现中简化为带有几何接触代理的尖端状态。我们在一个刻意简化的环境中评估该公式：一个合成平面血管模型，采用准静态杆模型和模拟投影，不使用临床或动物数据。在此环境中，信念状态模型以1.30毫米的均方根误差跟踪模拟尖端，同时以连续速率十五分之一的频率获取观测（每帧为0.97毫米，三十分之一频率为1.51毫米），报告的90%可信区间达到0.92的经验覆盖率，且信念衍生的接触风险估计以0.68的AUROC区分不安全接触事件。这些结果构成在简化模拟上的概念验证，而非临床就绪性的展示；其目的在于确立校准的信念（而非仅点估计精度）是稀疏成像世界模型必须提供的基本属性。
英文摘要
Endovascular catheter navigation relies on continuous fluoroscopy, exposing patients and clinical staff to ionizing radiation throughout the procedure. We investigate whether a physics-based world model can sustain the navigation task between deliberately sparse X-ray acquisitions, and whether the model can signal when its internal state estimate is no longer reliable. We formulate sparse-fluoroscopy navigation as a partially observable Markov decision process where a Cosserat rod simulator supplies transition dynamics, sparse noisy projections provide observations, and a particle filter maintains a belief over the device state, reduced in this implementation to a tip state with a geometric contact proxy. We evaluate this formulation in a deliberately simplified setting: a synthetic planar vessel phantom with a quasi-static rod model and simulated projections, without clinical or animal data. In this setting, the belief-state model tracks the simulated tip with a root mean square error of 1.30 mm while acquiring observations at one fifteenth of the continuous rate (0.97 mm at every frame, 1.51 mm at one thirtieth), reported 90 percent credible intervals achieve 0.92 empirical coverage, and the belief-derived contact risk estimate discriminates unsafe contact events with an AUROC of 0.68. These results constitute a proof of concept on a simplified simulation rather than a demonstration of clinical readiness; their purpose is to establish that calibrated belief, rather than point-estimate accuracy alone, is the essential property a sparse-imaging world model must deliver.
CommentsPresented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026) Workshop on Surgical Digital Twins (SurgTwin). 4 pages, 2 figures
