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Related Experiment Video

Updated: May 13, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
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Artificial Intelligence in Gastrointestinal Imaging: Advances and Applications.

Jaron J R Chong1, Anish Kirpalani2, Robert Moreland3

  • 1Department of Medical Imaging, Schulich School of Medicine and Dentistry, Western University, 800 Commissioners Road East, London, Ontario N6A 5W9, Canada.

Radiologic Clinics of North America
|April 12, 2025
PubMed
Summary

Artificial intelligence (AI) applications in gastrointestinal (GI) imaging are advancing, though slower than in other medical fields. This review covers AI concepts and its uses in GI tract imaging for better clinical implementation.

Keywords:
Artificial intelligenceComputer-aided diagnosisDeep learningGastrointestinal tractMachine learningMedical imaging

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Gastrointestinal (GI) Tract Imaging

Background:

  • AI has advanced medical imaging, but GI tract applications lag behind other regions.
  • Significant progress in AI for abdominal imaging, especially the GI system, is needed.
  • Understanding AI fundamentals is crucial for its integration into GI imaging.

Purpose of the Study:

  • To review foundational artificial intelligence (AI) concepts.
  • To highlight current AI applications in gastrointestinal (GI) tract imaging.
  • To discuss the implementation of AI in clinical practice and future development.

Main Methods:

  • Review of foundational AI concepts.
  • Examples of AI applications in acute & emergent GI imaging.
  • Discussion of AI in inflammatory bowel disease, oncology, and miscellaneous GI applications.

Main Results:

  • AI applications in GI imaging are diverse, covering emergent conditions, inflammatory bowel disease, and oncology.
  • Foundational AI concepts are essential for understanding its role in GI imaging.
  • Implementation challenges and future development strategies for AI in GI imaging are discussed.

Conclusions:

  • AI holds significant potential to advance gastrointestinal (GI) imaging diagnostics and patient care.
  • Addressing implementation barriers is key to accelerating AI adoption in clinical GI practice.
  • Continued research and development are vital for unlocking AI's full capabilities in the GI tract.