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.

翻译：手术导航通过估计患者解剖结构和手术器械的姿态来可视化相关术中信息，从而提供实时引导。在传统系统中，器械通常使用基准标记和固定式光学追踪系统进行追踪。增强现实技术进一步实现了直观的可视化，并推动了利用头戴式显示器内置传感器进行追踪的研究。然而，大多数现有方法依赖于清晰的视线，这在动态的手术室环境中难以维持，因为设备、手术工具和人员经常造成遮挡。本研究提出了一种框架，通过在动态场景图表示中融合多种传感模态，在遮挡条件下追踪手术器械。所提出的方法整合了具有不同精度水平和运动特性的追踪系统，同时实时估计追踪可靠性。实验结果表明，在存在遮挡的情况下，该框架提高了鲁棒性并增强了增强现实可视化的一致性。