A Bronchoscope Localization Method Using an Augmented Reality Co-Display of Real Bronchoscopy Images with a Virtual 3D Bronchial Tree Model

Sensors

Jiann-Der Lee¹  Ellen Su¹  Shih-Hong Li²  Jong-Chih Chien³ 

[1]Department of Electrical Engineering, Chang Gung University, Taoyuan 33302, Taiwan

[2]Department of Thoracic Medicine, Chang Gung Memorial Hospital at LinKou, Taoyuan 33305, Taiwan

[3]School of Informatics, Kainan University, Taoyuan 33857, Taiwan

关键词: augmented reality;    bronchoscopy;    localization;   

DOI  :  10.3390/s20236997

来源: DOAJ

【 摘 要 】

In recent years, Image-Guide Navigation Systems (IGNS) have become an important tool for various surgical operations. In the preparations for planning a surgical path, verifying the location of a lesion, etc., it is an essential tool; in operations such as bronchoscopy, which is the procedure for the inspection and retrieval of diagnostic samples for lung-related surgeries, it is even more so. The IGNS for bronchoscopy uses 2D-based images from a flexible bronchoscope to navigate through the bronchial airways in order to reach the targeted location. In this procedure, the accurate localization of the scope becomes very important, because incorrect information could potentially cause a surgeon to mistakenly direct the scope down the wrong passage. It would be a great aid for the surgeon to be able to visualize the bronchoscope images alongside the current location of the bronchoscope. For this purpose, in this paper, we propose a novel registration method to match real bronchoscopy images with virtual bronchoscope images from a 3D bronchial tree model built using computed tomography (CT) image stacks in order to obtain the current 3D position of the bronchoscope in the airways. This method is a combination of a novel position-tracking method using the current frames from the bronchoscope and the verification of the position of the real bronchoscope image against an image extracted from the 3D model using an adaptive-network-based fuzzy inference system (ANFIS)-based image matching method. Experimental results show that the proposed method performs better than the other methods used in the comparison.

【 授权许可】

Unknown