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GPU-based parallel fuzzy c-mean clustering model via genetic algorithm
Concurrency and computation, 2016-11, Vol.28 (16), p.4277-4290
Hung, Che-Lun
Wu, Yuan-Huai
2016
Details
Autor(en) / Beteiligte
Hung, Che-Lun
Wu, Yuan-Huai
Titel
GPU-based parallel fuzzy c-mean clustering model via genetic algorithm
Ist Teil von
Concurrency and computation, 2016-11, Vol.28 (16), p.4277-4290
Ort / Verlag
Blackwell Publishing Ltd
Erscheinungsjahr
2016
Link zum Volltext
Quelle
Wiley Online Library
Beschreibungen/Notizen
Summary Detection of white matter changes in brain tissue using magnetic resonance imaging has been an increasingly active and challenging research area in computational neuroscience. A genetic algorithm based on a fuzzy c‐mean clustering method (GAFCM) was applied to simulated images to separate foreground spot signal information from the background, and the results were compared. The strength of this algorithm was tested by evaluating the segmentation matching factor, coefficient of determination, concordance correlation, and gene expression values. The experimental results demonstrated that the segmentation ability of GAFCM was better than that of fuzzy c‐means and K‐means algorithms. However, GAFCM is computationally expensive. This study presents a new GPU‐based parallel GAFCM algorithm to improve the performance of GAFCM. The experimental results show that computational performance can be increased by a factor of approximately 20 over the CPU‐based GAFCM algorithm while maintaining the quality of the processed images. Thus, the proposed GPU‐based parallel GAFCM algorithm can achieve the same results and significantly decrease processing time. Copyright © 2015 John Wiley & Sons, Ltd.
Sprache
Englisch
Identifikatoren
ISSN: 1532-0626
eISSN: 1532-0634
DOI: 10.1002/cpe.3731
Titel-ID: cdi_proquest_miscellaneous_1845812412
Format
–
Schlagworte
Algorithms
,
Clustering
,
Computation
,
CUDA
,
Fuzzy
,
Fuzzy C-Mean
,
Gene expression
,
genetic algorithm
,
Genetic algorithms
,
GPU
,
Image segmentation
,
magnetic resonance
,
Mathematical models
,
white matter
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