Detecting and Measuring Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope

Xueshen Li, Yu Gan, David Duan, Xiao Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 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 languageEnglish
Title of host publication2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023
ISBN (Electronic)9781665473583
DOIs
StatePublished - 2023
Event20th IEEE International Symposium on Biomedical Imaging, ISBI 2023 - Cartagena, Colombia
Duration: 18 Apr 202321 Apr 2023

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2023-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference20th IEEE International Symposium on Biomedical Imaging, ISBI 2023
Country/TerritoryColombia
CityCartagena
Period18/04/2321/04/23

Keywords

  • Deep learning
  • Human gastric peristalsis
  • Magnetically controlled capsule endoscopy

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