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Interactive GPU Active Contours for Segmenting Inhomogeneous Objects

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

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Philip T.G. Jackson

Carl J. Nelson

Amar Nasrulloh

Boguslaw Obara


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.


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.

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


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