Clinical Performance of New Software to Automatically Detect Angioectasias in Small Bowel Capsule Endoscopy

摘要

Video capsule endoscopy (VCE) revolutionized the diagnosis and management of obscure gastrointestinal bleeding, though the rate of detection of small bowel lesions by the physician is still disappointing. Our group developed a novel algorithm (CMEMS-Uminho) to automatically detect angioectasias which display greater accuracy in VCE static frames than other methods previously published. We aimed to evaluate the algorithm overall performance and assess its diagnostic yield and usability in clinical practice.