Browse DORAS
Browse Theses
Search
Latest Additions
Creative Commons License
Except where otherwise noted, content on this site is licensed for use under a:

The use of 3D surface fitting for robust polyp detection and classification in CT colonography

Chowdhury, Tarik A. and Whelan, Paul F. and Ghita, Ovidiu (2006) The use of 3D surface fitting for robust polyp detection and classification in CT colonography. Computerized Medical Imaging and Graphics, 30 . pp. 427-436.

Full text available as:

[img]PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
439Kb

Abstract

In this paper we describe the development of a computationally efficient computer-aided detection (CAD) algorithm based on the evaluation of the surface morphology that is employed for the detection of colonic polyps in computed tomography (CT) colonography. Initial polyp candidate voxels were detected using the surface normal intersection values. These candidate voxels were clustered using the normal direction, convexity test, region growing and Gaussian distribution. The local colonic surface was classified as polyp or fold using a feature normalized nearest neighbor-hood classifier. The main merit of this paper is the methodology applied to select the robust features derived from the colon surface that have a high discriminative power for polyp/fold classification. The devised polyp detection scheme entails a low computational overhead (typically takes 2.20 minute per dataset) and shows 100% sensitivity for phantom polyps greater than 5mm. It also shows 100% sensitivity for real polyps larger than 10mm and 91.67% sensitivity for polyps between 5 to 10mm with an average of 4.5 false positives per dataset. The experimental data indicates that the proposed CAD polyp detection scheme outperforms other techniques that identify the polyps using features that sample the colon surface curvature especially when applied to low-dose datasets.

Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:computer vision; image analysis
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > National Biophotonics and Imaging Platform Ireland (NBIPI)
Research Initiatives and Centres > Research Institute for Networks and Communications Engineering (RINCE)
Publisher:Elsevier
ID Code:18333
Deposited On:24 Sep 2013 14:59 by Prof Paul Whelan. Last Modified 27 Oct 2017 09:56

Download statistics

Archive Staff Only: edit this record