Artificial Intelligence in Gastrointestinal Imaging : Advances and Applications - 11/04/25

Doi : 10.1016/j.rcl.2024.11.005

Jaron J.R. Chong, MD, MHI, FRCPC ^a, Anish Kirpalani, MASc, MD, FRCPC ^b,^c,^d, Robert Moreland, MD, MSc, FRCPC ^b,^c, Errol Colak, MD, FRCPC ^b,^c,^d,^⁎
^a Department of Medical Imaging, Schulich School of Medicine and Dentistry, Western University, 800 Commissioners Road East, London, Ontario N6A 5W9, Canada
^b Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
^c Department of Medical Imaging, St. Michael’s Hospital, Unity Health Toronto, 30 Bond Street, Toronto, Ontario M5B 1C9, Canada
^d Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada

^∗Corresponding author. Department of Medical Imaging, St. Michael’s Hospital, 30 Bond Street, Toronto, Ontario M5B 1C9, Canada.Department of Medical ImagingSt. Michael’s Hospital30 Bond StreetTorontoOntarioM5B 1C9Canada

Résumé

While artificial intelligence (AI) has shown considerable progress in many areas of medical imaging, applications in abdominal imaging, particularly for the gastrointestinal (GI) system, have notably lagged behind advancements in other body regions. This article reviews foundational concepts in AI and highlights examples of AI applications in GI tract imaging. The discussion on AI applications includes acute & emergent GI imaging, inflammatory bowel disease, oncology, and other miscellaneous applications. It concludes with a discussion of important considerations for implementing AI tools in clinical practice, and steps we can take to accelerate future developments in the field.

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Keywords : Artificial intelligence, Machine learning, Deep learning, Computer-aided diagnosis, Gastrointestinal tract, Medical imaging