Polyp-Alert: near real-time feedback during colonoscopy
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Updated: Apr 12, 2026

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
Yi Wang1, Wallapak Tavanapong1, Johnny Wong1
1Department of Computer Science, Iowa State University, Ames, IA 50011, USA.
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.
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