Title
Computer-aided detection of retroflexion in colonoscopy
Abstract
Colonoscopy is the most popular screening tool for colorectal cancer. Recent studies reported that retroflexion during colonoscopy improved polyp yields. 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 endoscopic images showing retroflexion. This problem has not been investigated in the literature. We propose new region features that encapsulate important properties of endoscope appearance during retroflexion. Our experimental results on 25 colonoscopy videos show that trained Decision Tree classifiers can effectively identify retroflexion in the rectum at 92.0% accuracy and 94.4% precision.
Year
DOI
Venue
2011
10.1109/CBMS.2011.5999137
CBMS
Keywords
Field
DocType
mucosa area,computer-aided detection,video signal processing,new region,endoscopic images,computerised instrumentation,decision tree classifier,endoscope appearance,internal mucosa visualization,image classification,screening tool,endoscope maneuver,colorectal cancer,colonoscopy improved polyp yield,colonoscopy video,colonoscopy videos,internal mucosa,computer aided retroflexion detection,decision trees,medical image processing,new method,colonoscopy,enabling visualization
Endoscope,Computer vision,Colonoscopy,Visualization,Computer science,Computer aided detection,Artificial intelligence
Conference
ISSN
ISBN
Citations 
1063-7125
978-1-4577-1189-3
6
PageRank 
References 
Authors
0.58
5
5
Name
Order
Citations
PageRank
Yi Wang11149.03
Wallapak Tavanapong2865.71
J. Wong3301.90
JungHwan Oh452044.87
P. C. de Groen5111.11