发表机构
Universidad de Zaragoza（萨拉戈萨大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
BronchoTop提出一种仅依赖RGB视频的实时拓扑定位框架，无需患者CT或外部传感器，通过四模块实现支气管镜导航，在真实数据上性能提升超20%，并开源算法与数据以促进发展。
AI 中文摘要
在诊断和治疗过程中，支气管镜在支气管树内的准确定位对于临床医生到达目标病灶、进行活检以及避免气道段误识别至关重要。然而，现有的导航系统通常依赖于患者特定的CT扫描或额外的外部传感器，这增加了成本、设置时间和患者的辐射暴露。本工作提出了BronchoTop，一个实时的、仅基于RGB的拓扑支气管镜定位框架，无需患者特定数据即可实现定位。BronchoTop通过四个模块估计相对于通用气道模型的镜体位置：管腔检测与跟踪、管腔-分支标签关联、概率性镜体位置估计以及切换验证。通过仅使用标准支气管镜视频输入，BronchoTop为医生提供实用、实时的导航辅助。在体模、模拟和真实数据上的评估展示了最先进的准确性，在真实支气管镜序列上将现有方法的性能提升了超过20%。BronchoTop是首个同时发布定位算法及所用全部真实数据，并提供生成额外模拟代码的框架，鼓励并促进了进一步的开发和基准测试。结果凸显了BronchoTop在临床和机器人支气管镜中增强手术安全性、效率和可及性的潜力。
英文摘要
Accurate localization of the bronchoscope within the bronchial tree is essential for clinicians to be able to reach target lesions, perform biopsies and avoid misidentification of airway segments during diagnostic and therapeutic procedures. However, existing navigation systems typically rely on patient-specific CT scans or additional external sensors, increasing cost, setup time and patient radiation exposure. This work presents BronchoTop, a real-time, RGB-only framework for topological bronchoscopy localization that eliminates the need for patient-specific data. BronchoTop estimates scope location relative to a generic airway model through four modules: lumen detection and tracking, lumen-branch label association, probabilistic scope location estimation, and switch verification. By using only standard bronchoscopy video input, BronchoTop provides practical, real-time navigational assistance to physicians. Evaluation on phantom, simulated and real data demonstrates state-of-the-art accuracy, improving existing approaches performance by over 20% on real bronchoscopy sequences. BronchoTop is the first published framework including both the localization algorithms as well as all the real data used, together with code to generate additional simulations, encouraging and facilitating further developments and benchmarking. The results highlight BronchoTop's potential to enhance procedural safety, efficiency and accessibility in clinical and robotic bronchoscopy.
