Objectives Poorly visualized images that appear during small bowel capsule endoscopy
(SBCE) can confuse the interpretation of small bowel lesions and increase the physician's …

BACKGROUND: Analyzing small-bowel capsule endoscopy (CE) images is time consuming.
OBJECTIVE: To determine the effect of reducing the number of images on reading time and …

Abstract Background and Aim Convolutional neural network (CNN) systems that
automatically detect abnormalities from small‐bowel capsule endoscopy (SBCE) images are …

Background In small-bowel capsule endoscopy (SBCE), differentiating masses (ie, lesions
of higher probability for neoplasia) requiring more aggressive intervention from bulges …

Aim Small bowel capsule endoscopy (CE) is a non-invasive and validated technique
allowing the visualization of the small intestine mucosa. It generated more than 40,000 …

Background & Aims Capsule endoscopy has revolutionized investigation of the small bowel.
However, this technique produces a video that is 8–10 hours long, so analysis is time …

Objectives Although several studies have shown the usefulness of artificial intelligence to
identify abnormalities in small‐bowel capsule endoscopy (SBCE) images, few studies have …

Background and study aims Capsule endoscopy (CE) is the preferred method for small
bowel (SB) exploration. Its diagnostic yield can be reduced by poor mucosal visualization …

BACKGROUND: Reading capsule endoscopy (CE) is time-consuming. The Express View
(EV)(IntroMedic, Seoul, Korea) software was designed to shorten CE video reading. Our …

Background and Aims Capsule endoscopy (CE) is a visual modality; hence, diagnosis relies
on image quality. We studied the contribution of image parameters to visualization quality …