Paper Info
Title
Polyp detection in Wireless Capsule Endoscopy videos based on image segmentation and geometric feature
Abstract
Wireless Capsule Endoscopy (WCE) is a relatively new technology (FDA approved in 2002) allowing doctors to view most of the small intestine. One of the most important goals of WCE is the early detection of colorectal polyps. In this paper an unsupervised method for the detection of polyps in WCE videos is presented. Our method involves watershed segmentation with a novel initial marker selection method based on Gabor texture features and K-means clustering. Geometric information from the resulting segments is extracted to identify polyp candidates. Initial experiments indicate that the proposed method can detect polyps with 100% sensitivity and over 81% specificity.
Year
DOI
Venue
2010
10.1109/ICASSP.2010.5495103
ICASSP
Keywords
Field
DocType
gabor filters,small intestine,gabor texture features,wireless capsule endoscopy,wireless capsule endoscopy videos,endoscopes,biomedical optical imaging,k-means clustering,image segmentation,colorectal polyps,watershed segmentation,feature extraction,geometric feature,polyp detection,biological organs,k-means,marker selection method,curvature,medical image processing,decision support systems,k means clustering,economic indicators,k means
Early detection,k-means clustering,Computer vision,Wireless,Pattern recognition,Computer science,Feature extraction,Image segmentation,Artificial intelligence,Capsule endoscopy,Cluster analysis
Conference
ISSN
ISBN
Citations 
1520-6149 E-ISBN : 978-1-4244-4296-6
978-1-4244-4296-6
3
PageRank 
References 
Authors
0.44
0
2
Name
Order
Citations
PageRank
Sae Hwang124717.88
M. Emre Celebi2124084.15