Simulation of manual and automatic navigation of magnetically controlled wireless capsule endoscopy examination of human gastric

Xueshen Li; Yu Gan; David Duan; Xiao Yang

doi:10.1117/12.3003356

Simulation of manual and automatic navigation of magnetically controlled wireless capsule endoscopy examination of human gastric

Xueshen Li
, Yu Gan
, David Duan
, Xiao Yang

Department of Biomedical Engineering

Stevens Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The magnetically controlled capsule endoscopy (MCCE) is an emerging modality for assessing gastrointestinal disorders due to its advantages. However, current assignments of MCCE rely on manual controlling and gastric landmarks, which are prone to omissions. We improve the scanning protocol of the MCCE in human gastric using both manual and automatic controlling methods. We design a quantitative scanning coverage ratio to measure the process of MCCE scanning within the human gastric. The proposed scanning coverage ratio is capable of guiding the manual and automatic scanning process of human gastric. Moreover, we design a deep reinforcement learning (DRL) controller for automatically navigating the capsule. Our DRL controller achieves a higher coverage ratio compared to previous research.

Original language	English
Title of host publication	Endoscopic Microscopy XIX
Editors	Guillermo J. Tearney, Thomas D. Wang, Melissa J. Suter
ISBN (Electronic)	9781510668997
DOIs	https://doi.org/10.1117/12.3003356
State	Published - 2024
Event	Endoscopic Microscopy XIX 2024 - San Francisco, United States Duration: 27 Jan 2024 → 28 Jan 2024

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	12820
ISSN (Print)	1605-7422

Conference

Conference	Endoscopic Microscopy XIX 2024
Country/Territory	United States
City	San Francisco
Period	27/01/24 → 28/01/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Deep learning
Human gastric examination
Magnetically controlled capsule endoscopy
Reinforcement learning

Access to Document

10.1117/12.3003356

Cite this

Li, X., Gan, Y., Duan, D., & Yang, X. (2024). Simulation of manual and automatic navigation of magnetically controlled wireless capsule endoscopy examination of human gastric. In G. J. Tearney, T. D. Wang, & M. J. Suter (Eds.), Endoscopic Microscopy XIX Article 1282006 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 12820). https://doi.org/10.1117/12.3003356

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title = "Simulation of manual and automatic navigation of magnetically controlled wireless capsule endoscopy examination of human gastric",

abstract = "The magnetically controlled capsule endoscopy (MCCE) is an emerging modality for assessing gastrointestinal disorders due to its advantages. However, current assignments of MCCE rely on manual controlling and gastric landmarks, which are prone to omissions. We improve the scanning protocol of the MCCE in human gastric using both manual and automatic controlling methods. We design a quantitative scanning coverage ratio to measure the process of MCCE scanning within the human gastric. The proposed scanning coverage ratio is capable of guiding the manual and automatic scanning process of human gastric. Moreover, we design a deep reinforcement learning (DRL) controller for automatically navigating the capsule. Our DRL controller achieves a higher coverage ratio compared to previous research.",

keywords = "Deep learning, Human gastric examination, Magnetically controlled capsule endoscopy, Reinforcement learning",

author = "Xueshen Li and Yu Gan and David Duan and Xiao Yang",

note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Endoscopic Microscopy XIX 2024 ; Conference date: 27-01-2024 Through 28-01-2024",

year = "2024",

doi = "10.1117/12.3003356",

language = "English",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

editor = "Tearney, \{Guillermo J.\} and Wang, \{Thomas D.\} and Suter, \{Melissa J.\}",

booktitle = "Endoscopic Microscopy XIX",

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Li, X, Gan, Y, Duan, D & Yang, X 2024, Simulation of manual and automatic navigation of magnetically controlled wireless capsule endoscopy examination of human gastric. in GJ Tearney, TD Wang & MJ Suter (eds), Endoscopic Microscopy XIX., 1282006, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 12820, Endoscopic Microscopy XIX 2024, San Francisco, United States, 27/01/24. https://doi.org/10.1117/12.3003356

Simulation of manual and automatic navigation of magnetically controlled wireless capsule endoscopy examination of human gastric. / Li, Xueshen; Gan, Yu; Duan, David et al.
Endoscopic Microscopy XIX. ed. / Guillermo J. Tearney; Thomas D. Wang; Melissa J. Suter. 2024. 1282006 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 12820).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Simulation of manual and automatic navigation of magnetically controlled wireless capsule endoscopy examination of human gastric

AU - Li, Xueshen

AU - Gan, Yu

AU - Duan, David

AU - Yang, Xiao

N1 - Publisher Copyright: © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

PY - 2024

Y1 - 2024

N2 - The magnetically controlled capsule endoscopy (MCCE) is an emerging modality for assessing gastrointestinal disorders due to its advantages. However, current assignments of MCCE rely on manual controlling and gastric landmarks, which are prone to omissions. We improve the scanning protocol of the MCCE in human gastric using both manual and automatic controlling methods. We design a quantitative scanning coverage ratio to measure the process of MCCE scanning within the human gastric. The proposed scanning coverage ratio is capable of guiding the manual and automatic scanning process of human gastric. Moreover, we design a deep reinforcement learning (DRL) controller for automatically navigating the capsule. Our DRL controller achieves a higher coverage ratio compared to previous research.

AB - The magnetically controlled capsule endoscopy (MCCE) is an emerging modality for assessing gastrointestinal disorders due to its advantages. However, current assignments of MCCE rely on manual controlling and gastric landmarks, which are prone to omissions. We improve the scanning protocol of the MCCE in human gastric using both manual and automatic controlling methods. We design a quantitative scanning coverage ratio to measure the process of MCCE scanning within the human gastric. The proposed scanning coverage ratio is capable of guiding the manual and automatic scanning process of human gastric. Moreover, we design a deep reinforcement learning (DRL) controller for automatically navigating the capsule. Our DRL controller achieves a higher coverage ratio compared to previous research.

KW - Deep learning

KW - Human gastric examination

KW - Magnetically controlled capsule endoscopy

KW - Reinforcement learning

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UR - https://www.scopus.com/pages/publications/85190952548#tab=citedBy

U2 - 10.1117/12.3003356

DO - 10.1117/12.3003356

M3 - Conference contribution

AN - SCOPUS:85190952548

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Endoscopic Microscopy XIX

A2 - Tearney, Guillermo J.

A2 - Wang, Thomas D.

A2 - Suter, Melissa J.

T2 - Endoscopic Microscopy XIX 2024

Y2 - 27 January 2024 through 28 January 2024

ER -

Simulation of manual and automatic navigation of magnetically controlled wireless capsule endoscopy examination of human gastric

Abstract

Publication series

Conference

UN SDGs

Keywords

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