Development of a Real-time Colorectal Tumor Classification System for Narrow-band Imaging zoom-videoendoscopy
This system addresses the need for early detection and treatment of colorectal cancer by assisting endoscopists, though it appears incremental as it builds on existing pretrained classifiers.
The researchers tackled the problem of providing objective, real-time assistance during colorectal endoscopy by developing a computer-aided diagnosis system that classifies video streams from narrow-band imaging zoom-videoendoscopy, with experimental results indicating efficient performance in actual examinations.
Colorectal endoscopy is important for the early detection and treatment of colorectal cancer and is used worldwide. A computer-aided diagnosis (CAD) system that provides an objective measure to endoscopists during colorectal endoscopic examinations would be of great value. In this study, we describe a newly developed CAD system that provides real-time objective measures. Our system captures the video stream from an endoscopic system and transfers it to a desktop computer. The captured video stream is then classified by a pretrained classifier and the results are displayed on a monitor. The experimental results show that our developed system works efficiently in actual endoscopic examinations and is medically significant.