Computer-aided system for Polyp detection in wireless capsule endoscopy images

Wireless capsule endoscopy (WCE) is a contemporary method that can view the entire intestine. Because of its advantages, it has been widely used. However, physicians demand an automatic way to shorten the time required to analyze the produced images (over 55,000 images in one examination for one patient). In this paper a recognition system for CE imaging has been developed to automatically detect and recognize polyps. The proposed method is founded upon the extraction of Local Fractal Dimension (LFD) features over the detected SIFT Keypoints, these characteristics are then concatenated with Uniform Local Binary Pattern (LBPu) or Complete LBP (CLBP) so as to integrate the texture information. Various classifiers were used to distinguish the normal images from the polyp ones. Experimental results on a publicly available dataset demonstrate that the presented scheme can achieve 97.98% accuracy.