title: A comparative study of shape features for polyp detection in wireless capsule endoscopy images.
abstract: Wireless capsule endoscopy (WCE) has been gradually employed in hospitals because it can directly view the entire small bowel of a human body for the first time. However, a troublesome problem related to this new technology is that too many images produced by WCE will take a lot of efforts for doctors to inspect. In this paper, we propose a comparative study of shape features aiming for intestinal polyp detection for WCE images. As polyps exhibit strong shape characteristics, also a powerful clue used by physicians, we investigate two kinds of shape features, MEPG-7 region-based shape descriptor and Zernike moments, in our study. With multi-layer perceptron neural network as the classifier, experiments on our present image data show that it is promising to employ both Zernike moments and MEPG-7 region-based shape descriptor as the shape features to recognize the intestinal polyp regions, and a better performance is obtained by the Zernike moments based shape features.
authors: Department of Electronic Engineering at The Chinese University of Hong Kong, Hong Kong SAR, China. bpli@ee.cuhk.edu.hk
authors: Baopu
authors: B
authors: Li
authors: Max Q H
authors: MQ
authors: Meng
authors: Lisheng
authors: L
authors: Xu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001699:Biometry / Q000379:methods; D053705:Capsule Endoscopes; D053704:Capsule Endoscopy / Q000379:methods*; D003952:Diagnostic Imaging / Q000379:methods; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007417:Intestinal Polyps / Q000175:diagnosis* / Q000473:pathology; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity