Interactive GPU active contours for segmenting inhomogeneous objects

Willcocks, C. G., Jackson, P. T.G., Nelson, C. , Nasrulloh, A. V. and Obara, B. (2019) Interactive GPU active contours for segmenting inhomogeneous objects. Journal of Real-Time Image Processing, 16(6), pp. 2305-2318. (doi: 10.1007/s11554-017-0740-1)

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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:Articles
Keywords:Segmentation, active contours, level set methods, GPU, medical applications, biological applications.
Glasgow Author(s) Enlighten ID:Nelson, Dr Chas
Authors: Willcocks, C. G., Jackson, P. T.G., Nelson, C., Nasrulloh, A. V., and Obara, B.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
College/School:College of Science and Engineering > School of Physics and Astronomy
Journal Name:Journal of Real-Time Image Processing
ISSN (Online):1861-8219
Published Online:26 December 2017
Copyright Holders:Copyright © 2017 The Authors
First Published:First published in Journal of Real-Time Image Processing 16(6): 2305-2318
Publisher Policy:Reproduced under a Creative Commons License

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