BronchoTop: Bronchoscopy Navigation via RGB-Only Topological Localization

2026-09-23

AI Summary

为解决支气管镜定位问题，本文提出仅使用RGB视频的BronchoTop框架，通过四个模块实现精准定位，提高临床操作的安全性和效率。

Abstract

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.

Problem

• bronchoscopy
• localization
• patient-specific CT scans
• external sensors
• radiation exposure

Innovation

• RGB-only localization
• topological bronchoscopy
• real-time navigation
• generic airway model