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Interactive GPU active contours for segmenting inhomogeneous objects

Lookup NU author(s): Dr Chris Willcocks, Phillip Jackson, Professor Boguslaw Obara

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2018, The Author(s). 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.


Publication metadata

Author(s): Willcocks CG, Jackson PTG, Nelson CJ, Nasrulloh AV, Obara B

Publication type: Article

Publication status: Published

Journal: Journal of Real-Time Image Processing

Year: 2019

Volume: 16

Issue: 6

Pages: 2305-2318

Print publication date: 01/12/2019

Online publication date: 26/12/2017

Acceptance date: 27/11/2017

Date deposited: 29/04/2021

ISSN (print): 1861-8200

ISSN (electronic): 1861-8219

Publisher: Springer

URL: https://doi.org/10.1007/s11554-017-0740-1

DOI: 10.1007/s11554-017-0740-1


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