ArticleSensors (Basel, Switzerland)2020
A Bronchoscope Localization Method Using an Augmented Reality Co-Display of Real Bronchoscopy Images with a Virtual 3D Bronchial Tree Model.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- A bronchoscopic navigation method based on neural radiation fields.International journal of computer assisted radiology and surgery · 2024Article
- The insufficiency of CT examination in early detection of central lung squamous cell carcinoma and squamous epithelial precancerous lesions.BMC cancer · 2024Article
- Diagnostic Performance of Electromagnetic Navigation versus Virtual Navigation Bronchoscopy-Guided Biopsy for Pulmonary Lesions in a Single Institution: Potential Role of Artificial Intelligence for Navigation Planning.Diagnostics (Basel, Switzerland) · 2023Article
- Measurement Systems for Use in the Navigation of the Cannula-Guide Assembly within the Deep Regions of the Bronchial Tree.Sensors (Basel, Switzerland) · 2023Article
- Deep learning for anatomical interpretation of video bronchoscopy images.Scientific reports · 2021Article
- Modern Trends and Applications of Intelligent Methods in Biomedical Signal and Image Processing.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.