Background and Objective: The quality of colonoscopy has been a subject of interest in the gastroenterology community for over two decades. High-quality colonoscopy leads to high polyp detection rates, reducing mortality associated with colorectal cancer. Methods: This paper describes the development and deployment of Endoscopic Multimedia Information System (EMIS), computer-aided software that provides real-time feedback on colonoscopy quality such as the endoscopist's techniques in inspecting the colon. On the contrary, most other software in this field aims to recognize polyps. The deployed version of EMIS includes new analysis components using Convolutional Neural Networks and new types of visual feedback. EMIS gives feedback only when an important change in the quality of the examination occurs. We present first-hand technical and operational challenges faced during our three-center trial and current solutions. Results: This work provides valuable information for others attempting to implement real-time feedback in routine colonoscopy screening.
|Original language||English (US)|
|Journal||Biomedical Signal Processing and Control|
|State||Published - May 2023|
Bibliographical noteFunding Information:
We thank Dr. Cynthia Ko of University of Washington Medical Center, Dr. Mark Lazarev of John Hopkins University, Brandon Snailer, Jaber Salem, Elena-Bianca Ciobanu, Mariola Sadowska, and James Villar-Mead for their help with data collection and organization during the trial; and, Gavin Kijkul for his assistance with model training and support.
This work was supported in part by the National Institutes of Health (NIH) [Grant No 1R01DK106130-01A1].
© 2023 Elsevier Ltd
- Computer-aided analysis
- Polyp detection rate
- Real-time feedback