Application of SLAM in endoscopic imaging

Yuxuan Xi

doi:10.54254/2755-2721/12/20230290

Research Article

Open access

Published on 25 September 2023

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Xi,Y. (2023). Application of SLAM in endoscopic imaging. Applied and Computational Engineering,12,28-33.

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Application of SLAM in endoscopic imaging

Yuxuan Xi *^,1,

¹ Xi’an University of Technology

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/12/20230290

Abstract

This paper presents the utilization of Simultaneous Localization and Mapping (SLAM) technology in medical endoscopic imaging. The fundamental components, hardware configuration, and process of SLAM are introduced in detail, with a focus on sensor acquisition, data preprocessing, feature extraction and matching, state estimation and update, map construction, and optimization modules. The application of SLAM in the medical field is then discussed, specifically highlighting real-time localization and reconstruction of endoscopic imaging. The integration of SLAM technology can assist doctors in accurately identifying the site of lesions, thereby enhancing surgical precision and safety. Furthermore, the paper introduces various commonly used SLAM algorithms, including the Kalman filter, extended Kalman filter, particle filter, optimization algorithms, among others. It emphasizes the significance of algorithm selection and optimization tailored to different scenarios and requirements. In conclusion, the application of SLAM technology in medical endoscopy imaging holds immense potential, offering improved accuracy and visualization during surgical procedures. This technology provides valuable support for doctors in diagnosis and treatment, ultimately enhancing patient outcomes.

Keywords

SLAM technology, endoscopic imaging, medical application.

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References

[1]. Huo, J., Li, M., Wang, Z., Yuan, B., Yang, Q., Wang, L. (2023). Panoramic endoscopic imaging technology and its application. Chinese Optics.

[2]. Xu, R. (2022). Abdominal cavity 3D texture reconstruction based on monocular visual SLAM. Harbin University of Science and Technology.

[3]. Wu, H. Xu, R., Wang, A., Yu, X., Yan, K., You, Z., Zhao, L., Liu, H. (2021). A review of 3D reconstruction of human body cavity based on computer vision. Computer Engineering.

[4]. Guo, W., Mei, J., Sun, R., Yu, S., Sun, L. (2021). Triangulation based human body map construction method of endoscopic intestinal surgery machine. Robot.

[5]. Guo, W. (2021). Modeling of human intestinal environment for endoscopic surgical robot navigation. Soochow University.

[6]. Qiu, L., & Ren, H. (2020). Endoscope navigation with SLAM-based registration to computed tomography for transoral surgery. International Journal of Intelligent Robotics and Applications, 4(2), 252–263. https://doi.org/10.1007/s41315-020-00127-2

[7]. Dai, C. (2020). Research on cavity 3D modeling method based on ORB-SLAM. Harbin University of Science and Technology.

[8]. Gu, H. (2020). Endoscopic intubation aid decision making in human narrow passages based on deep learning. University of Electronic Science and Technology of China.

[9]. Xie, C., Yao, T., Wang, J., & Liu, Q. (2020). Endoscope localization and gastrointestinal feature map construction based on monocular SLAM technology. Journal of Infection and Public Health, 13(9), 1314–1321. https://doi.org/10.1016/j.jiph.2019.06.028

[10]. Richard， J.， Chen., Taylor, L. Bobrow., Thomas., Athey., Faisal, Mahmood., Nicholas, J., Durr. (2019) SLAM Endoscopy enhanced by adversarial depth prediction. CoRR.

Cite this article

Xi,Y. (2023). Application of SLAM in endoscopic imaging. Applied and Computational Engineering,12,28-33.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Mechatronics and Smart Systems

Conference website: https://2023.confmss.org/

ISBN：978-1-83558-013-4(Print) / 978-1-83558-014-1(Online)

Conference date: 24 June 2023

Editor：Seyed Ghaffar, Alan Wang

Series: Applied and Computational Engineering

Volume number: Vol.12

ISSN：2755-2721(Print) / 2755-273X(Online)

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