Endoscope 3D reconstruction based on ORB-SLAM

Research Article
Open access

Endoscope 3D reconstruction based on ORB-SLAM

Baichuan Zhang 1*
  • 1 Nanjing University of Aeronautics and Astronautics    
  • *corresponding author Birchard-Z@nuaa.edu.cn
Published on 25 September 2023 | https://doi.org/10.54254/2755-2721/12/20230300
ACE Vol.12
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-013-4
ISBN (Online): 978-1-83558-014-1

Abstract

Minimal invasive surgery (MIS) is the mainstream trend in developing surgical technology. As the endoscope is a significant tool in the surgical process, whether it can track the inner cavity and realize accurate real-time 3D reconstruction has a vital impact on the smooth progress of MIS. However, there are still problems in the endoscopic environment, such as severe image distortion, the effect of lighting conditions, and the inability to extract lumen textures. Orinted fast and rotated brief simultaneous localization and mapping (ORB-SLAM) is currently a relatively advanced simultaneous localization and mapping (SLAM) method with better performance. The ORB-SLAM-based endoscope 3D reconstruction method can improve performance and overcome the challenge of endoscope 3D reconstruction. This paper will first introduce several existing endoscope 3D reconstruction methods based on ORB-SLAM and analyze the limitations and issues of these methods through their experimental results. Then the paper will explore the solutions to the defects in this method from other methods and compare the characteristics and the result of experiments. Secondly, through the summary of the above methods and the introduction of the integration of the ORB-SLAM-based methods and other current advanced technologies, the future development trend and huge development potential of ORB-SLAM-based endoscopic 3D reconstruction are introduced. This paper will be of profound affection to further improve the optimization and application of the ORB-SLAM-based endoscope 3D reconstruction method.

Keywords:

orinted fast, rotated brief simultaneous localization, mapping, endoscope, 3D reconstruction.

Zhang,B. (2023). Endoscope 3D reconstruction based on ORB-SLAM. Applied and Computational Engineering,12,78-86.
Export citation

References

[1]. Chia-Hsiang Wu, Yung-Nien Sun, & Chien-Chen Chang. (2007). Three-Dimensional Modeling From Endoscopic Video Using Geometric Constraints Via Feature Positioning. IEEE Transactions on Biomedical Engineering, 54(7), 1199-1211. https://doi.org/10.1109/TBME.2006.889767

[2]. Mountney, P., Stoyanov, D., Davison, A., & Yang, G.-Z. (2006). Simultaneous Stereoscope Localization and Soft-Tissue Mapping for Minimal Invasive Surgery. In R. Larsen, M. Nielsen, & J. Sporring (Eds.), Medical Image Computing and Computer-Assisted Intervention-MICCAI 2006 (Vol. 4190, pp. 347-354). Springer Berlin Heidelberg. https://doi.org/10.1007/11866565_43

[3]. Davison. (2003). Real-time simultaneous localisation and mapping with a single camera. Proceedings Ninth IEEE International Conference on Computer Vision, 1403-1410 vol.2. https://doi.org/10.1109/ICCV.2003.1238654

[4]. Grasa, O. G., Civera, J., Guemes, A., Munoz, V., & Montiel, J. M. M. (n.d.). EKF Monocular SLAM 3D Modeling, Measuring and Augmented Reality from Endoscope Image Sequences.

[5]. Mountney, P., & Yang, G.-Z. (2010). Motion Compensated SLAM for Image Guided Surgery. In T. Jiang, N. Navab, J. P. W. Pluim, & M. A. Viergever (Eds.), Medical Image Computing and Computer-Assisted Intervention-MICCAI 2010 (Vol. 6362, pp. 496-504). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15745-5_61

[6]. Rublee, E., Rabaud, V., Konolige, K., & Bradski, G. (2011). ORB: An efficient alternative to SIFT or SURF. 2011 International Conference on Computer Vision, 2564-2571. https://doi.org/10.1109/ICCV.2011.6126544

[7]. Hutchison, D., Kanade, T., Kittler, J., Kleinberg, J. M., Mattern, F., Mitchell, J. C., Naor, M., Nierstrasz, O., Pandu Rangan, C., Steffen, B., Sudan, M., Terzopoulos, D., Tygar, D., Vardi, M. Y., Weikum, G., Calonder, M., Lepetit, V., Strecha, C., & Fua, P. (2010). BRIEF: Binary Robust Independent Elementary Features. In K. Daniilidis, P. Maragos, & N. Paragios (Eds.), Computer Vision - ECCV 2010 (Vol. 6314, pp. 778-792). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15561-1_56

[8]. Lin, B., Johnson, A., Qian, X., Sanchez, J., & Sun, Y. (2013). Simultaneous Tracking, 3D Reconstruction and Deforming Point Detection for Stereoscope Guided Surgery. In H. Liao, C. A. Linte, K. Masamune, T. M. Peters, & G. Zheng (Eds.), Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions (Vol. 8090, pp. 35-44). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-40843-4_5

[9]. Klein, G., & Murray, D. (2007). Parallel Tracking and Mapping for Small AR Workspaces. 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, 1-10. https://doi.org/10.1109/ISMAR.2007.4538852

[10]. Mur-Artal, R., Montiel, J. M. M., & Tardos, J. D. (2015). ORB-SLAM: A Versatile and Accurate Monocular SLAM System. IEEE Transactions on Robotics, 31(5), 1147-1163. https://doi.org/10.1109/TRO.2015.2463671

[11]. Mur-Artal, R., & Tardos, J. D. (2017). ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras. IEEE Transactions on Robotics, 33(5), 1255-1262. https://doi.org/10.1109/TRO.2017.2705103

[12]. Campos, C., Elvira, R., Rodríguez, J. J. G., Montiel, J. M. M., & Tardós, J. D. (2021). ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM. IEEE Transactions on Robotics, 37(6), 1874-1890. https://doi.org/10.1109/TRO.2021.3075644

[13]. Mahmoud, N., Cirauqui, I., Hostettler, A., Doignon, C., Soler, L., Marescaux, J., & Montiel, J. M. M. (2017). ORBSLAM-Based Endoscope Tracking and 3D Reconstruction. In T. Peters, G.-Z. Yang, N. Navab, K. Mori, X. Luo, T. Reichl, & J. McLeod (Eds.), Computer-Assisted and Robotic Endoscopy (Vol. 10170, pp. 72-83). Springer International Publishing. https://doi.org/10.1007/978-3-319-54057-3_7

[14]. Chen, W., Liao, X., Sun, Y., & Wang, Q. (2020). Improved ORB-SLAM Based 3D Dense Reconstruction for Monocular Endoscopic Image. 2020 International Conference on Virtual Reality and Visualization (ICVRV), 101-106. https://doi.org/10.1109/ICVRV51359.2020.00030

[15]. Wang, K., & Shen, S. (2018). Adaptive Baseline Monocular Dense Mapping with Inter-Frame Depth Propagation. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 3225-3232. https://doi.org/10.1109/IROS.2018.8593936

[16]. Mahmoud, N., Collins, T., Hostettler, A., Soler, L., Doignon, C., & Montiel, J. M. M. (2019). Live Tracking and Dense Reconstruction for Handheld Monocular Endoscopy. IEEE Transactions on Medical Imaging, 38(1), 79-89. https://doi.org/10.1109/TMI.2018.2856109

[17]. Huo, J., Zhou, C., Yuan, B., Yang, Q., & Wang, L. (2023). Real-Time Dense Reconstruction with Binocular Endoscopy Based on StereoNet and ORB-SLAM. Sensors, 23(4), 2074. https://doi.org/10.3390/s23042074

[18]. Turan, M., Almalioglu, Y., Konukoglu, E., & Sitti, M. (2017). A Deep Learning Based 6 Degree-of-Freedom Localization Method for Endoscopic Capsule Robots (arXiv:1705.05435). arXiv. http://arxiv.org/abs/1705.05435

[19]. Qiu, L., & Ren, H. (2018). Endoscope Navigation and 3D Reconstruction of Oral Cavity by Visual SLAM with Mitigated Data Scarcity. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2278-22787. https://doi.org/10.1109/CVPRW.2018.00295

Cite this article

Zhang,B. (2023). Endoscope 3D reconstruction based on ORB-SLAM. Applied and Computational Engineering,12,78-86.

Data availability

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

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

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

ISBN：978-1-83558-013-4(Print) / 978-1-83558-014-1(Online)
Editor：Seyed Ghaffar, Alan Wang
Conference website: https://2023.confmss.org/
Conference date: 24 June 2023
Series: Applied and Computational Engineering
Volume number: Vol.12
ISSN：2755-2721(Print) / 2755-273X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).

References

[1]. Chia-Hsiang Wu, Yung-Nien Sun, & Chien-Chen Chang. (2007). Three-Dimensional Modeling From Endoscopic Video Using Geometric Constraints Via Feature Positioning. IEEE Transactions on Biomedical Engineering, 54(7), 1199-1211. https://doi.org/10.1109/TBME.2006.889767

[2]. Mountney, P., Stoyanov, D., Davison, A., & Yang, G.-Z. (2006). Simultaneous Stereoscope Localization and Soft-Tissue Mapping for Minimal Invasive Surgery. In R. Larsen, M. Nielsen, & J. Sporring (Eds.), Medical Image Computing and Computer-Assisted Intervention-MICCAI 2006 (Vol. 4190, pp. 347-354). Springer Berlin Heidelberg. https://doi.org/10.1007/11866565_43

[3]. Davison. (2003). Real-time simultaneous localisation and mapping with a single camera. Proceedings Ninth IEEE International Conference on Computer Vision, 1403-1410 vol.2. https://doi.org/10.1109/ICCV.2003.1238654

[4]. Grasa, O. G., Civera, J., Guemes, A., Munoz, V., & Montiel, J. M. M. (n.d.). EKF Monocular SLAM 3D Modeling, Measuring and Augmented Reality from Endoscope Image Sequences.

[5]. Mountney, P., & Yang, G.-Z. (2010). Motion Compensated SLAM for Image Guided Surgery. In T. Jiang, N. Navab, J. P. W. Pluim, & M. A. Viergever (Eds.), Medical Image Computing and Computer-Assisted Intervention-MICCAI 2010 (Vol. 6362, pp. 496-504). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15745-5_61

[6]. Rublee, E., Rabaud, V., Konolige, K., & Bradski, G. (2011). ORB: An efficient alternative to SIFT or SURF. 2011 International Conference on Computer Vision, 2564-2571. https://doi.org/10.1109/ICCV.2011.6126544

[7]. Hutchison, D., Kanade, T., Kittler, J., Kleinberg, J. M., Mattern, F., Mitchell, J. C., Naor, M., Nierstrasz, O., Pandu Rangan, C., Steffen, B., Sudan, M., Terzopoulos, D., Tygar, D., Vardi, M. Y., Weikum, G., Calonder, M., Lepetit, V., Strecha, C., & Fua, P. (2010). BRIEF: Binary Robust Independent Elementary Features. In K. Daniilidis, P. Maragos, & N. Paragios (Eds.), Computer Vision - ECCV 2010 (Vol. 6314, pp. 778-792). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15561-1_56

[8]. Lin, B., Johnson, A., Qian, X., Sanchez, J., & Sun, Y. (2013). Simultaneous Tracking, 3D Reconstruction and Deforming Point Detection for Stereoscope Guided Surgery. In H. Liao, C. A. Linte, K. Masamune, T. M. Peters, & G. Zheng (Eds.), Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions (Vol. 8090, pp. 35-44). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-40843-4_5

[9]. Klein, G., & Murray, D. (2007). Parallel Tracking and Mapping for Small AR Workspaces. 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, 1-10. https://doi.org/10.1109/ISMAR.2007.4538852

[10]. Mur-Artal, R., Montiel, J. M. M., & Tardos, J. D. (2015). ORB-SLAM: A Versatile and Accurate Monocular SLAM System. IEEE Transactions on Robotics, 31(5), 1147-1163. https://doi.org/10.1109/TRO.2015.2463671

[11]. Mur-Artal, R., & Tardos, J. D. (2017). ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras. IEEE Transactions on Robotics, 33(5), 1255-1262. https://doi.org/10.1109/TRO.2017.2705103

[12]. Campos, C., Elvira, R., Rodríguez, J. J. G., Montiel, J. M. M., & Tardós, J. D. (2021). ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM. IEEE Transactions on Robotics, 37(6), 1874-1890. https://doi.org/10.1109/TRO.2021.3075644

[13]. Mahmoud, N., Cirauqui, I., Hostettler, A., Doignon, C., Soler, L., Marescaux, J., & Montiel, J. M. M. (2017). ORBSLAM-Based Endoscope Tracking and 3D Reconstruction. In T. Peters, G.-Z. Yang, N. Navab, K. Mori, X. Luo, T. Reichl, & J. McLeod (Eds.), Computer-Assisted and Robotic Endoscopy (Vol. 10170, pp. 72-83). Springer International Publishing. https://doi.org/10.1007/978-3-319-54057-3_7

[14]. Chen, W., Liao, X., Sun, Y., & Wang, Q. (2020). Improved ORB-SLAM Based 3D Dense Reconstruction for Monocular Endoscopic Image. 2020 International Conference on Virtual Reality and Visualization (ICVRV), 101-106. https://doi.org/10.1109/ICVRV51359.2020.00030

[15]. Wang, K., & Shen, S. (2018). Adaptive Baseline Monocular Dense Mapping with Inter-Frame Depth Propagation. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 3225-3232. https://doi.org/10.1109/IROS.2018.8593936

[16]. Mahmoud, N., Collins, T., Hostettler, A., Soler, L., Doignon, C., & Montiel, J. M. M. (2019). Live Tracking and Dense Reconstruction for Handheld Monocular Endoscopy. IEEE Transactions on Medical Imaging, 38(1), 79-89. https://doi.org/10.1109/TMI.2018.2856109

[17]. Huo, J., Zhou, C., Yuan, B., Yang, Q., & Wang, L. (2023). Real-Time Dense Reconstruction with Binocular Endoscopy Based on StereoNet and ORB-SLAM. Sensors, 23(4), 2074. https://doi.org/10.3390/s23042074

[18]. Turan, M., Almalioglu, Y., Konukoglu, E., & Sitti, M. (2017). A Deep Learning Based 6 Degree-of-Freedom Localization Method for Endoscopic Capsule Robots (arXiv:1705.05435). arXiv. http://arxiv.org/abs/1705.05435

[19]. Qiu, L., & Ren, H. (2018). Endoscope Navigation and 3D Reconstruction of Oral Cavity by Visual SLAM with Mitigated Data Scarcity. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2278-22787. https://doi.org/10.1109/CVPRW.2018.00295

For authors
Guide for authors Policies for authors Aims and scope Subscription Open access policy
For editors
Policies for editors Editorial board
For reviewers
Policies for reviewers Privacy policy

Cookies are used by this site.
Copyright © 2024 EWA Publishing, its licensors, and contributors. All rights reserved, including text and data mining, AI training, and similar technologies.