Paper Info
Title
Automatic classification of images with appendiceal orifice in colonoscopy videos.
Abstract
Colonoscopy is an endoscopic technique that allows a physician to inspect the inside of the human colon. In current practice, videos captured from colonoscopic procedures are not routinely stored for either manual or automated post-procedure analysis. In this paper, we introduce new algorithms for automated detection of the presence of the shape of the opening of the appendix in a colonoscopy video frame. The appearance of the appendix in colonoscopy videos indicates traversal of the colon, which is an important measurement for evaluating the quality of colonoscopic procedures. The proposed techniques are valuable for (1) establishment of an effective content-based retrieval system to facilitate endoscopic research and education; and (2) assessment and improvement of the procedural skills of endoscopists, both in training and practice.
Year
DOI
Venue
2006
10.1109/IEMBS.2006.260686
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
Keywords
DocType
Volume
biological organs,biomedical optical imaging,content-based retrieval,endoscopes,image classification,medical image processing,video signal processing,appendiceal orifice,automatic image classification,colonoscopy video frame,content-based retrieval system,endoscopic technique
Conference
1
ISSN
Citations 
PageRank 
1557-170X
3
0.43
References 
Authors
8
6
Name
Order
Citations
PageRank
Yu Cao160.89
Danyu Liu229819.96
Wallapak Tavanapong353563.27
Johnny Wong450049.19
JungHwan Oh552044.87
Piet C. De Groen637229.89