Detecting and Measuring Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope

Xueshen Li; Yu Gan; David Duan; Xiao Yang

doi:10.1109/ISBI53787.2023.10230671

Detecting and Measuring Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope

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

2 Scopus citations

Abstract

Magnetically controlled capsule endoscope (MCCE) is an emerging tool for the diagnosis of gastric diseases with the advantages of comfort, safety, and no anesthesia. In this paper, we develop algorithms to detect and measure human gastric peristalsis (contraction wave) using video sequences acquired by MCCE. We develop a spatial-temporal deep learning algorithm to detect gastric contraction waves and measure human gastric peristalsis periods. The quality of MCCE video sequences is prone to camera motion. We design a camera motion detector (CMD) to process the MCCE video sequences, mitigating the camera movement during MCCE examination. To the best of our knowledge, we are the first to propose computer vision-based solutions to both detect and measure periods of human gastric peristalsis. Our methods have great potential in assisting the diagnosis of gastric diseases by evaluating gastric motility.

Original language	English
Title of host publication	2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023
ISBN (Electronic)	9781665473583
DOIs	https://doi.org/10.1109/ISBI53787.2023.10230671
State	Published - 2023
Event	20th IEEE International Symposium on Biomedical Imaging, ISBI 2023 - Cartagena, Colombia Duration: 18 Apr 2023 → 21 Apr 2023

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2023-April
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	20th IEEE International Symposium on Biomedical Imaging, ISBI 2023
Country/Territory	Colombia
City	Cartagena
Period	18/04/23 → 21/04/23

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 peristalsis
Magnetically controlled capsule endoscopy

Access to Document

10.1109/ISBI53787.2023.10230671

Cite this

@inproceedings{1cf3009ae9a640e288a83966771bcb45,

title = "Detecting and Measuring Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope",

abstract = "Magnetically controlled capsule endoscope (MCCE) is an emerging tool for the diagnosis of gastric diseases with the advantages of comfort, safety, and no anesthesia. In this paper, we develop algorithms to detect and measure human gastric peristalsis (contraction wave) using video sequences acquired by MCCE. We develop a spatial-temporal deep learning algorithm to detect gastric contraction waves and measure human gastric peristalsis periods. The quality of MCCE video sequences is prone to camera motion. We design a camera motion detector (CMD) to process the MCCE video sequences, mitigating the camera movement during MCCE examination. To the best of our knowledge, we are the first to propose computer vision-based solutions to both detect and measure periods of human gastric peristalsis. Our methods have great potential in assisting the diagnosis of gastric diseases by evaluating gastric motility.",

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

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

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 20th IEEE International Symposium on Biomedical Imaging, ISBI 2023 ; Conference date: 18-04-2023 Through 21-04-2023",

year = "2023",

doi = "10.1109/ISBI53787.2023.10230671",

language = "English",

series = "Proceedings - International Symposium on Biomedical Imaging",

booktitle = "2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023",

}

Li, X, Gan, Y, Duan, D & Yang, X 2023, Detecting and Measuring Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope. in 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. Proceedings - International Symposium on Biomedical Imaging, vol. 2023-April, 20th IEEE International Symposium on Biomedical Imaging, ISBI 2023, Cartagena, Colombia, 18/04/23. https://doi.org/10.1109/ISBI53787.2023.10230671

Detecting and Measuring Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope. / Li, Xueshen; Gan, Yu; Duan, David et al.
2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. 2023. (Proceedings - International Symposium on Biomedical Imaging; Vol. 2023-April).

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

TY - GEN

T1 - Detecting and Measuring Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope

AU - Li, Xueshen

AU - Gan, Yu

AU - Duan, David

AU - Yang, Xiao

PY - 2023

Y1 - 2023

N2 - Magnetically controlled capsule endoscope (MCCE) is an emerging tool for the diagnosis of gastric diseases with the advantages of comfort, safety, and no anesthesia. In this paper, we develop algorithms to detect and measure human gastric peristalsis (contraction wave) using video sequences acquired by MCCE. We develop a spatial-temporal deep learning algorithm to detect gastric contraction waves and measure human gastric peristalsis periods. The quality of MCCE video sequences is prone to camera motion. We design a camera motion detector (CMD) to process the MCCE video sequences, mitigating the camera movement during MCCE examination. To the best of our knowledge, we are the first to propose computer vision-based solutions to both detect and measure periods of human gastric peristalsis. Our methods have great potential in assisting the diagnosis of gastric diseases by evaluating gastric motility.

AB - Magnetically controlled capsule endoscope (MCCE) is an emerging tool for the diagnosis of gastric diseases with the advantages of comfort, safety, and no anesthesia. In this paper, we develop algorithms to detect and measure human gastric peristalsis (contraction wave) using video sequences acquired by MCCE. We develop a spatial-temporal deep learning algorithm to detect gastric contraction waves and measure human gastric peristalsis periods. The quality of MCCE video sequences is prone to camera motion. We design a camera motion detector (CMD) to process the MCCE video sequences, mitigating the camera movement during MCCE examination. To the best of our knowledge, we are the first to propose computer vision-based solutions to both detect and measure periods of human gastric peristalsis. Our methods have great potential in assisting the diagnosis of gastric diseases by evaluating gastric motility.

KW - Deep learning

KW - Human gastric peristalsis

KW - Magnetically controlled capsule endoscopy

UR - https://www.scopus.com/pages/publications/85172141203

UR - https://www.scopus.com/pages/publications/85172141203#tab=citedBy

U2 - 10.1109/ISBI53787.2023.10230671

DO - 10.1109/ISBI53787.2023.10230671

M3 - Conference contribution

AN - SCOPUS:85172141203

T3 - Proceedings - International Symposium on Biomedical Imaging

BT - 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023

T2 - 20th IEEE International Symposium on Biomedical Imaging, ISBI 2023

Y2 - 18 April 2023 through 21 April 2023

ER -

Detecting and Measuring Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope

Abstract

Publication series

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UN SDGs

Keywords

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