Polyp-Alert: Near real-time feedback during colonoscopy

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

Research output: Contribution to journalArticlepeer-review

94 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)164-179
Number of pages16
JournalComputer Methods and Programs in Biomedicine
Issue number3
StatePublished - Jul 1 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 Elsevier Ireland Ltd.


  • Colonoscopy
  • Medical imaging/video
  • Near Real-time
  • Polyp detection


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