无需患者扫描，用图像实现支气管镜导航的拓扑定位。
Online Topological Localization for Navigation Assistance in Bronchoscopy
- 基于图像构建支气管树拓扑定位流程，无需患者CT扫描。
- 仅在模拟数据上训练，仍能在真实数据上表现优于现有方法。
- 适合临床导航辅助，尤其适用于缺乏扫描资源的场景。
支气管镜检查是呼吸科基础操作，医生需在复杂的支气管树中导航至目标区域。当前导航依赖患者术前CT重建三维气道模型，并结合传感器或图像配准追踪内窥镜位置，虽精度高但需额外扫描和训练。实际应用中，精确度量定位并非必需，基于通用气道模型的拓扑定位已足够辅助。本文提出一种基于图像的支气管镜拓扑定位流程，无需患者CT扫描。模型仅在模拟数据上训练，避免真实数据标注成本，具备良好泛化能力。实验结果表明，该方法在真实数据测试序列上性能超越现有方法。
原文摘要 · Abstract (English)
Video bronchoscopy is a fundamental procedure in respiratory medicine, where medical experts navigate through the bronchial tree of a patient to diagnose or operate the patient. Surgeons need to determine the position of the scope as they go through the airway until they reach the area of interest. This task is very challenging for practitioners due to the complex bronchial tree structure and varying doctor experience and training. Navigation assistance to locate the bronchoscope during the procedure can improve its outcome. Currently used techniques for navigational guidance commonly rely on previous CT scans of the patient to obtain a 3D model of the airway, followed by tracking of the scope with additional sensors or image registration. These methods obtain accurate locations but imply additional setup, scans and training. Accurate metric localization is not always required, and a topological localization with regard to a generic airway model can often suffice to assist the surgeon with navigation. We present an image-based bronchoscopy topological localization pipeline to provide navigation assistance during the procedure, with no need of patient CT scan. Our approach is trained only on phantom data, eliminating the high cost of real data labeling, and presents good generalization capabilities. The results obtained surpass existing methods, particularly on real data test sequences.
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