Detecting Human Gastric Peristalsis Using Magnetically Controlled Capsule Endoscope via Deep Learning

Xueshen Li, Yu Gan, David Duan, Xiao Yang

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

2 Scopus citations

Abstract

Gastric motility disorders are caused by abnormal muscle contractions which may impede the digestive process. Traditional approaches for evaluating human gastric motility have limitations, including discomfort, use of sedation, risk of radiation exposure, and confusion in interpretation. Magnetically controlled capsule endoscopy (MCCE) provides a new way to evaluate human gastric with the advantages of comfort, safety, and no anesthesia. In this paper, we develop deep learning algorithms to detect human gastric waves captured by MCCE. We demonstrate promising experimental results both qualitatively and quantitatively. Our methods have great potential to assist in the diagnosis of human gastric disease by evaluating gastric motility.

Original languageEnglish
Title of host publicationMedical Imaging 2023
Subtitle of host publicationImage Processing
EditorsOlivier Colliot, Ivana Isgum
ISBN (Electronic)9781510660335
DOIs
StatePublished - 2023
EventMedical Imaging 2023: Image Processing - San Diego, United States
Duration: 19 Feb 202323 Feb 2023

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume12464
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2023: Image Processing
Country/TerritoryUnited States
CitySan Diego
Period19/02/2323/02/23

Keywords

  • Deep learning
  • Gastric motility disorders
  • Magnetically controlled capsule endoscopy
  • Medical image analysis

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