多视角融合追踪手术器械，解决术中遮挡难题。
Extend Your Horizon: A Device-Agnostic Surgical Tool Tracking Framework with Multi-View Optimization for Augmented Reality
- 构建动态场景图融合多模态传感器数据
- 在遮挡下保持跟踪精度与可视化一致性
- 适合需高鲁棒性导航的智能手术系统
手术导航通过估计患者解剖结构和手术器械的位姿，实现实时引导并可视化术中信息。传统系统依赖于标记物和固定光学跟踪系统（OTS）。增强现实（AR）进一步实现了直观可视化，推动使用嵌入头戴式显示器（HMD）的传感器进行追踪。然而，现有方法大多依赖清晰视野，在动态手术室环境中难以维持，因设备、器械和人员频繁造成遮挡。本文提出一种设备无关的手术器械追踪框架，通过在动态场景图表示中融合多传感模态，实现遮挡下的稳定追踪。该方法整合不同精度和运动特性的追踪系统，并实时评估追踪可靠性。实验结果表明，在遮挡条件下，系统显著提升了鲁棒性与AR可视化的一致性。
原文摘要 · Abstract (English)
Surgical navigation provides real-time guidance by estimating the pose of patient anatomy and surgical instruments to visualize relevant intraoperative information. In conventional systems, instruments are typically tracked using fiducial markers and stationary optical tracking systems (OTS). Augmented reality (AR) has further enabled intuitive visualization and motivated tracking using sensors embedded in head-mounted displays (HMDs). However, most existing approaches rely on a clear line of sight, which is difficult to maintain in dynamic operating room environments due to frequent occlusions caused by equipment, surgical tools, and personnel. This work introduces a framework for tracking surgical instruments under occlusion by fusing multiple sensing modalities within a dynamic scene graph representation. The proposed approach integrates tracking systems with different accuracy levels and motion characteristics while estimating tracking reliability in real time. Experimental results demonstrate improved robustness and enhanced consistency of AR visualization in the presence of occlusions.
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