Wireless Capsule Endoscopy and Endoscopic Imaging: A Survey on Various Methodologies Presented

Abstract

The purpose of this study was to serve as a reference for further research improvements and to address the current level of maturity of each methodology from its maximum capabilities. This paper discussed the following: automatic detection of intestinal juices in wireless capsule video endoscopy; neural networks-based approach; model of deformable rings for aiding the WCE video interpretation and reporting; digestive organ automatic image classification; WCE blood detection using expectation maximization clustering; discriminate tissues color distributions; color- and texture-based GI tissue discrimination; topographic segmentation and transit time estimation for endoscopic capsule exams; automated tissue classification; colonoscopic diagnosis using online learning and differential evolution; computer-aided tumor detection using color wavelet features; versatile coLD detection system for colorectal lesions; images sequences; blood-based abnormalities detection; and other related topics.