Cookies

We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.


Durham Research Online
You are in:

Interactive GPU active contours for segmenting inhomogeneous objects.

Willcocks, Chris G. and Jackson, Philip T.G. and Nelson, Carl J. and Nasrulloh, Amar and Obara, Boguslaw (2017) 'Interactive GPU active contours for segmenting inhomogeneous objects.', Journal of real-time image processing. .

Abstract

We present a segmentation software package primarily targeting medical and biological applications, with a high level of visual feedback and several usability enhancements over existing packages. Specifically, we provide a substantially faster GPU implementation of the local Gaussian distribution fitting energy model, which can segment inhomogeneous objects with poorly defined boundaries as often encountered in biomedical images. We also provide interactive brushes to guide the segmentation process in a semiautomated framework. The speed of our implementation allows us to visualize the active surface in real time with a built-in ray tracer, where users may halt evolution at any time step to correct implausible segmentation by painting new blocking regions or new seeds. Quantitative and qualitative validation is presented, demonstrating the practical efficacy of our interactive elements for a variety of real-world datasets.

Item Type:Article
Full text:(AM) Accepted Manuscript
First Live Deposit - 28 November 2017
Available under License - Creative Commons Attribution.
Download PDF
(14571Kb)
Full text:(VoR) Version of Record
Download PDF (Advance online version)
(2775Kb)
Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1007/s11554-017-0740-1
Publisher statement:This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Record Created:28 Nov 2017 14:13
Last Modified:22 Jan 2018 15:14

Social bookmarking: del.icio.usConnoteaBibSonomyCiteULikeFacebookTwitterExport: EndNote, Zotero | BibTex
Look up in GoogleScholar | Find in a UK Library