DocumentCode :
63567
Title :
Near Real-Time Retroflexion Detection in Colonoscopy
Author :
Yi Wang ; Tavanapong, W. ; Wong, Johnson ; JungHwan Oh ; de Groen, P.C.
Author_Institution :
Dept. of Comput. Sci., Iowa State Univ., Ames, IA, USA
Volume :
17
Issue :
1
fYear :
2013
fDate :
Jan. 2013
Firstpage :
143
Lastpage :
152
Abstract :
Colonoscopy is the most popular screening tool for colorectal cancer. Recent studies reported that retroflexion during colonoscopy helped to detect more polyps. Retroflexion is an endoscope maneuver that enables visualization of internal mucosa along the shaft of the endoscope, enabling visualization of the mucosa area that is difficult to see with typical forward viewing. This paper describes our new method that detects retroflexion during colonoscopy. We propose region shape and location (RSL) features and edgeless edge cross-section profile (ECSP) features that encapsulate important properties of endoscope appearance and edge information during retroflexion. Our experimental results on 50 colonoscopy test videos show that a simple ensemble classifier using both ECSP and RSL features can effectively identify retroflexion in terms of analysis time and detection rate.
Keywords :
biological organs; diseases; edge detection; endoscopes; feature extraction; image classification; medical image processing; retroreflectors; shape recognition; ECSP feature; RSL features; analysis time; colonoscopy test video; colorectal cancer screening tool; detection rate; edgeless edge cross-section profile feature; endoscope appearance properties; endoscope maneuver; endoscope shaft; internal mucosa visualization; near real-time retroflexion detection; polyp detection; region shape and location feature; retroflexion edge information; simple ensemble classifier; typical forward viewing; Colon; Colonoscopy; Endoscopes; Feature extraction; Image edge detection; Shape; Videos; Colonoscopy; edge cross-section profile (ECSP); medical image analysis; retroflexion detection; Algorithms; Colon; Colonic Polyps; Colonoscopy; Humans; Image Processing, Computer-Assisted; Video Recording;
fLanguage :
English
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
Publisher :
ieee
ISSN :
2168-2194
Type :
jour
DOI :
10.1109/TITB.2012.2226595
Filename :
6341086
Link To Document :
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