Polyp-Alert: near real-time feedback during colonoscopy

Yi Wang; Wallapak Tavanapong; Johnny Wong; Jung Hwan Oh; Piet C de Groen

doi:10.1016/j.cmpb.2015.04.002

Polyp-Alert: near real-time feedback during colonoscopy

Comput Methods Programs Biomed. 2015 Jul;120(3):164-79. doi: 10.1016/j.cmpb.2015.04.002. Epub 2015 Apr 18.

Authors

Yi Wang¹, Wallapak Tavanapong², Johnny Wong¹, Jung Hwan Oh³, Piet C de Groen⁴

Affiliations

¹ Department of Computer Science, Iowa State University, Ames, IA 50011, USA.
² Department of Computer Science, Iowa State University, Ames, IA 50011, USA. Electronic address: tavanapo@cs.iastate.edu.
³ Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, USA.
⁴ Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN 55905, USA.

PMID: 25952076
DOI: 10.1016/j.cmpb.2015.04.002

Abstract

We present a software system called "Polyp-Alert" to assist the endoscopist find polyps by providing visual feedback during colonoscopy. Polyp-Alert employs our previous edge-cross-section visual features and a rule-based classifier to detect a polyp edge-an edge along the contour of a polyp. The technique employs tracking of detected polyp edge(s) to group a sequence of images covering the same polyp(s) as one polyp shot. In our experiments, the software correctly detected 97.7% (42 of 43) of polyp shots on 53 randomly selected video files of entire colonoscopy procedures. However, Polyp-Alert incorrectly marked only 4.3% of a full-length colonoscopy procedure as showing a polyp when they do not. The test data set consists of about 18 h worth of video data from Olympus and Fujinon endoscopes. The technique is extensible to other brands of colonoscopes. Furthermore, Polyp-Alert can provide as high as ten feedbacks per second for a smooth display of feedback. The performance of our system is by far the most promising to potentially assist the endoscopist find more polyps in clinical practice during a routine screening colonoscopy.

Keywords: Colonoscopy; Medical imaging/video; Near Real-time; Polyp detection.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Colonic Polyps / diagnosis*
Colonoscopy*
Humans