Artificial intelligence in capsule endoscopy for detection of ulcers and erosions

Shabana F. Pasha, Jean Christophe Saurin

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Capsule endoscopy (CE) has revolutionized the diagnosis of small bowel (SB) disorders by allowing noninvasive visualization of the entire SB and colonic mucosa. However, several limitations remain in the diagnosis and monitoring of Crohn’s disease (CD) due to the low specificity of CE and need for manual review of the entire study. Artificial intelligence (AI) has many potential roles, including automated and improved detection of inflammatory lesions, diagnosis and monitoring of CD, evaluation for dysplasia and malignancy, prediction of fibrostenotic complications, and auto-documentation of reports. There is emerging data with proof-of-concept studies on the utility of AI in CD. These concepts and algorithms will require robust testing and validation before they can be reliably applied in clinical practice.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Capsule Endoscopy
Subtitle of host publicationA Gamechanger for a Groundbreaking Technique
PublisherElsevier
Pages101-119
Number of pages19
ISBN (Electronic)9780323996471
ISBN (Print)9780323996488
DOIs
StatePublished - Jan 1 2023

Keywords

  • artificial intelligence
  • Capsule endoscopy
  • convolutional neural network
  • Crohn’s disease
  • erosion
  • image enhanced endoscopy
  • machine learning
  • ulcer

ASJC Scopus subject areas

  • General Agricultural and Biological Sciences
  • General Biochemistry, Genetics and Molecular Biology

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