{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T16:09:12Z","timestamp":1790179752893,"version":"4.1.0"},"reference-count":64,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,6,16]],"date-time":"2025-06-16T00:00:00Z","timestamp":1750032000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Artificial intelligence (AI) is rapidly transforming imaging modalities in inflammatory bowel disease (IBD), particularly in endoscopy and ultrasound. Despite their critical roles, both modalities are challenged by interobserver variability, subjectivity, and accessibility issues. AI offers significant potential to address these limitations by enhancing lesion detection, standardizing disease activity scoring, and supporting clinical decision-making. In endoscopy, deep convolutional neural networks have achieved high accuracy in detecting mucosal abnormalities and grading disease severity, reducing observer dependency and improving diagnostic consistency. AI-assisted colonoscopy systems have also demonstrated improvements in procedural quality metrics, including adenoma detection rates and withdrawal times. Similarly, AI applications in intestinal ultrasound show promise in automating measurements of bowel wall thickness, assessing vascularity, and distinguishing between inflammatory and fibrotic strictures, which are critical for tailored therapy decisions. Video capsule endoscopy has likewise benefited from AI, reducing interpretation times and enhancing the detection of subtle lesions. Despite these advancements, implementation challenges, including dataset quality, standardization, AI interpretability, clinician acceptance, and regulatory and ethical considerations, must be carefully addressed. The current review focuses on the most recent developments in the integration of AI into experimental designs, medical devices, and clinical workflows for optimizing diagnostic accuracy, treatment strategies, and patient outcomes in IBD management.<\/jats:p>","DOI":"10.3390\/jcm14124291","type":"journal-article","created":{"date-parts":[[2025,6,16]],"date-time":"2025-06-16T14:03:11Z","timestamp":1750082591000},"page":"4291","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Artificial Intelligence in Endoscopic and Ultrasound Imaging for Inflammatory Bowel Disease"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5872-8630","authenticated-orcid":false,"given":"Rare\u0219","family":"Cr\u0103ciun","sequence":"first","affiliation":[{"name":"Department of Internal Medicine, \u201cIuliu Ha\u021bieganu\u201d University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania"},{"name":"Department of Gastroenterology, \u201cProf. Dr. Octavian Fodor\u201d Institute of Gastroenterology and Hepatology, 19-21 Croitorilor Street, 400162 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5993-4092","authenticated-orcid":false,"given":"Andreea Livia","family":"Bumbu","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, \u201cIuliu Ha\u021bieganu\u201d University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania"},{"name":"Department of Gastroenterology, 1st Medical Clinic, 3-5 Clinicilor Street, 400006 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2246-6293","authenticated-orcid":false,"given":"Vlad Andrei","family":"Ichim","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, \u201cIuliu Ha\u021bieganu\u201d University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania"},{"name":"Department of Gastroenterology, 1st Medical Clinic, 3-5 Clinicilor Street, 400006 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5975-0779","authenticated-orcid":false,"given":"Alina Ioana","family":"Tan\u021b\u0103u","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, \u201cIuliu Ha\u021bieganu\u201d University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania"},{"name":"Department of Gastroenterology, 4th Medical Clinic, 18 Republicii Street, 400015 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cristian","family":"Tefas","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, \u201cIuliu Ha\u021bieganu\u201d University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania"},{"name":"Department of Gastroenterology, \u201cProf. Dr. Octavian Fodor\u201d Institute of Gastroenterology and Hepatology, 19-21 Croitorilor Street, 400162 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3407","DOI":"10.1016\/j.csbj.2024.09.003","article-title":"Artificial Intelligence: A New Tool in the Pathologist\u2019s Armamentarium for the Diagnosis of IBD","volume":"23","author":"Cannarozzi","year":"2024","journal-title":"Comput. 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