Title
Note on Feature Selection for Polyp Detection in CT Colonography
Abstract
In this paper we describe a computer aided detection (CAD) algorithm for robust detection of polyps in computed tomography (CT) colonography. The devised algorithm identifies suspicious polyp candidate surfaces using the surface normal intersection, Hough transform, 3D histogram analysis, region growing and a convexity test. From these detected surfaces we extract statistical and morphological features in order to evaluate if the surface in question is a polyp or fold. In order to devise the optimal classification scheme the performance of two different classifiers are evaluated when the algorithm is applied to synthetic and real patient data. The experimental results indicate that the overall polyp detection performance shows sensitivity higher than 92% for polyps larger than 5mm with an average of 4.7 to 6.0 false positives per dataset.
Year
DOI
Venue
2006
10.1109/ICPR.2006.870
Pattern Recognition, 2006. ICPR 2006. 18th International Conference
Keywords
Field
DocType
Hough transforms,biological organs,computerised tomography,feature extraction,image classification,medical image processing,stereo image processing,3D histogram analysis,CT colonography,Hough transform,computed tomography,computer aided detection,convexity test,feature extraction,feature selection,optimal classification,polyp detection,region growing,surface normal intersection
CAD,Computer vision,Histogram,Pattern recognition,Feature selection,Computer science,Hough transform,Feature extraction,Artificial intelligence,Region growing,Contextual image classification,False positive paradox
Conference
Volume
ISSN
ISBN
1
1051-4651
0-7695-2521-0
Citations 
PageRank 
References 
0
0.34
3
Authors
4
Name
Order
Citations
PageRank
Tarik A. Chowdhury1173.12
Ovidiu Ghita223418.12
Paul F. Whelan356139.95
abhilash a miranda400.34