Table of Contents
Diagnostic and Therapeutic Endoscopy
Volume 2011, Article ID 182435, 7 pages
Research Article

Automatic Polyp Detection in Pillcam Colon 2 Capsule Images and Videos: Preliminary Feasibility Report

1Department of Gastroenterology, University Hospital of Coimbra and Faculty of Medicine, University of Coimbra, 3000-075 Coimbra, Portugal
2CMUC, Department of Mathematics, University of Coimbra, 3001-454 Coimbra, Portugal
3Department of Mathematics, The University of Texas at Austin, Austin, TX 78712, USA

Received 31 December 2010; Revised 13 March 2011; Accepted 13 March 2011

Academic Editor: Wahid Wassef

Copyright © 2011 Pedro N. Figueiredo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. The aim of this work is to present an automatic colorectal polyp detection scheme for capsule endoscopy. Methods. PillCam COLON2 capsule-based images and videos were used in our study. The database consists of full exam videos from five patients. The algorithm is based on the assumption that the polyps show up as a protrusion in the captured images and is expressed by means of a P-value, defined by geometrical features. Results. Seventeen PillCam COLON2 capsule videos are included, containing frames with polyps, flat lesions, diverticula, bubbles, and trash liquids. Polyps larger than 1 cm express a P-value higher than 2000, and 80% of the polyps show a P-value higher than 500. Diverticula, bubbles, trash liquids, and flat lesions were correctly interpreted by the algorithm as nonprotruding images. Conclusions. These preliminary results suggest that the proposed geometry-based polyp detection scheme works well, not only by allowing the detection of polyps but also by differentiating them from nonprotruding images found in the films.