Interactive GPU Active Contours for Segmenting Inhomogeneous Objects

Willcocks, Chris G.; Jackson, Philip T.G.; Nelson, Carl J.; Nasrulloh, Amar; Obara, Boguslaw

doi:10.1007/s11554-017-0740-1

Interactive GPU Active Contours for Segmenting Inhomogeneous Objects

Willcocks, Chris G.; Jackson, Philip T.G.; Nelson, Carl J.; Nasrulloh, Amar; Obara, Boguslaw

Authors

Dr Chris Willcocks christopher.g.willcocks@durham.ac.uk
Associate Professor

Philip T.G. Jackson

Carl J. Nelson

Amar Nasrulloh

Boguslaw Obara

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.

Citation

Willcocks, C. G., Jackson, P. T., Nelson, C. J., Nasrulloh, A., & Obara, B. (2019). Interactive GPU Active Contours for Segmenting Inhomogeneous Objects. Journal of Real-Time Image Processing, 16(6), 2305-2318. https://doi.org/10.1007/s11554-017-0740-1

Journal Article Type	Article
Acceptance Date	Nov 27, 2017
Online Publication Date	Dec 26, 2017
Publication Date	Dec 31, 2019
Deposit Date	May 30, 2017
Publicly Available Date	Nov 28, 2017
Journal	Journal of Real-Time Image Processing
Print ISSN	1861-8200
Electronic ISSN	1861-8219
Publisher	Springer
Peer Reviewed	Peer Reviewed
Volume	16
Issue	6
Pages	2305-2318
DOI	https://doi.org/10.1007/s11554-017-0740-1

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