Detection and Segmentation of Colonic Polyps on Implicit Isosurfaces by Second Principal Curvature Flow

Journal article (2010)

Authors

C. Van Wijk

V.F. Van Ravesteijn

F.M. Vos

L.J. Van Vliet

Department

Imaging Science and Technology () (TU Delft)

DOI: https://doi.org/doi:10.1109/TMI.2009.2031323

Image analysis Biomedical image processing Partial differential equation (PDE) Polyp detection Surface evolution

To reference this document use:

http://resolver.tudelft.nl/uuid:ae45e55b-1374-4d81-9df5-3104cf5e2905

More Info

expand_more

Published Date

03-03-2010

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Source:

IEEE Transactions on Medical Imaging, 29 (3), 2010

Faculty

Applied Sciences

Department

Imaging Science and Technology

Abstract

Today’s computer aided detection systems for computed tomography colonography (CTC) enable automated detection and segmentation of colorectal polyps.We present a paradigm shift by proposing a method that measures the amount of protrudedness of a candidate object in a scale adaptive fashion. One of the main results is that the performance of the candidate detection depends only on one parameter, the amount of protrusion. Additionally the method yields correct polyp segmentation without the need of an additional segmentation step. The supervised pattern recognition involves a clear distinction between size related features and features related to shape or intensity. A Mahalanobis transformation of the latter facilitates ranking of the objects using a logistic classifier. We evaluate two implementations of the method on 84 patients with a total of 57 polyps larger than or equal to 6 mm.We obtained a performance of 95% sensitivity at four false positives per scan for polyps larger than or equal to 6 mm.

Files

VanWijk_2010.pdf

(pdf | 1.89 Mb)