A visual SLAM-based bronchoscope tracking scheme for bronchoscopic navigation
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ORIGINAL ARTICLE
A visual SLAM-based bronchoscope tracking scheme for bronchoscopic navigation Cheng Wang1 · Masahiro Oda1 · Yuichiro Hayashi1 · Benjamin Villard1 · Takayuki Kitasaka2 · Hirotsugu Takabatake3 · Masaki Mori4 · Hirotoshi Honma4 · Hiroshi Natori5 · Kensaku Mori1 Received: 13 January 2020 / Accepted: 21 July 2020 © CARS 2020
Abstract Purpose Due to the complex anatomical structure of bronchi and the resembling inner surfaces of airway lumina, bronchoscopic examinations require additional 3D navigational information to assist the physicians. A bronchoscopic navigation system provides the position of the endoscope in CT images with augmented anatomical information. To overcome the shortcomings of previous navigation systems, we propose using a technique known as visual simultaneous localization and mapping (SLAM) to improve bronchoscope tracking in navigation systems. Methods We propose an improved version of the visual SLAM algorithm and use it to estimate nt-specific bronchoscopic video as input. We improve the tracking procedure by adding more narrow criteria in feature matching to avoid mismatches. For validation, we collected several trials of bronchoscopic videos with a bronchoscope camera by exploring synthetic rubber bronchus phantoms. We simulated breath by adding periodic force to deform the phantom. We compared the camera positions from visual SLAM with the manually created ground truth of the camera pose. The number of successfully tracked frames was also compared between the original SLAM and the proposed method. Results We successfully tracked 29,559 frames at a speed of 80 ms per frame. This corresponds to 78.1% of all acquired frames. The average root mean square error for our technique was 3.02 mm, while that for the original was 3.61 mm. Conclusion We present a novel methodology using visual SLAM for bronchoscope tracking. Our experimental results showed that it is feasible to use visual SLAM for the estimation of the bronchoscope camera pose during bronchoscopic navigation. Our proposed method tracked more frames and showed higher accuracy than the original technique did. Future work will include combining the tracking results with virtual bronchoscopy and validation with in vivo cases. Keywords Endoscope tracking · Visual SLAM · Motion estimation · Bronchoscopic navigation
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Cheng Wang [email protected] Kensaku Mori [email protected] http://www.newves.org/
Masahiro Oda [email protected] Yuichiro Hayashi [email protected]
1
Benjamin Villard [email protected]
Graduate School of Informatics, Nagoya university, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan
2
Takayuki Kitasaka [email protected]
School of Information Science, Aichi Institute of Technology, Yachigusa 1247, Yakusa-cho, Toyota, Aichi 470-0356, Japan
3
Department of Respiratory Medicine, Sapporo Minami-Sankyo Hospital, Nishi-6-chome, Minami-3-jo, Chuo-ku, Sapporo, Hokkaido 060-0063, Japan
4
Department of Respiratory Medicine, Sapporo-Kosei
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