Real-Time Computer-Aided Detection for colorectal neoplasia or only small polyps?

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Abstract

Adenoma detection rate is the constant subject of research but quality improvement with a link to better attention to all polyps detection, has a chance to reduce interval colorectal cancers rates. Thus a presented point of view at an integrating computer-aided detection (CADe) of polyps with high-accuracy in real time colonoscopy challenges a quality improvement in performance of colonoscopy. Colonoscopy with the integration of deep learning methodology, artificial intelligence (AI) with computer – aided detection system (CADe) have been assessed for bowel cancer screening in an effort to enhance adenoma detection rates. A few studies were described and their results showed that CADe is able to increase screening sensitivity. Detection of adenomatous polyps which associate with a potential risk of progression to colorectal cancer and their removal is expected to reduce cancer incidence and mortality. However, so far, AI does not increase detection of cancer or large adenomatous polyps but contribute to detection of small pre-cancerous polyps.