Background and study aims Computer-aided diagnostic tools using deep neural networks
are efficient for detection of lesions in endoscopy but require a huge number of images. The …

Abstract The progress in Computer Aided Diagnosis (CADx) of Wireless Capsule
Endoscopy (WCE) is thwarted by the lack of data. The inadequacy in richly representative …

Several computer-based medical systems have been proposed for automatic detection of
abnormalities in a variety of medical imaging domains. The majority of these systems are …

The lack of generalizability of deep learning approaches for the automated diagnosis of
pathologies in Wireless Capsule Endoscopy (WCE) has prevented any significant …

Unlike wired endoscopy, capsule endoscopy requires additional time for a clinical specialist
to review the operation and examine the lesions. To reduce the tedious review time and …

Wireless video capsule endoscopy (CE) is a noninvasive endoscopic technique developed
in the mid 1990s that has been used to visualize a wide spectrum of pathologic conditions of …

Capsule endoscopy (CE) has revolutionized the investigation of various small-bowel
abnormalities. About 10 devices fabricated by 5 companies are commercially available. As …

participating centers in France. The study met the approval of the French Data Protection
Authority. In total, more than 4,000 CE pooled studies were reviewed and an impressive …

Conclusion In conclusion, the novelty of AI-based polyp detection and characterization has
generated great expectations for a more universal AI approach to gastrointestinal …

Background Artificial intelligence (AI) has made considerable progress in image recognition,
especially in the analysis of endoscopic images. The availability of large‐scale annotated …