Medical Image Segmentation Using a Combination of Lattice Boltzmann Method and Fuzzy Clustering Based on GPU CUDA Parallel Processing

The rapid development of computer technology has had a significant influence on advances in medical science. This development concerns segmenting medical images that can be used to help doctors diagnose patient diseases. The boundary between objects contained in an image is captured using the level...

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Autores principales:	Ignasius Boli Suban, Suyoto Suyoto, Pranowo Pranowo
Formato:	article
Lenguaje:	EN
Publicado:	International Association of Online Engineering (IAOE) 2021
Materias:	lattice boltzmann fuzzy clustering gpu Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/434de85535374fddb44f85171047a20c
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spelling	oai:doaj.org-article:434de85535374fddb44f85171047a20c2021-11-16T07:23:28ZMedical Image Segmentation Using a Combination of Lattice Boltzmann Method and Fuzzy Clustering Based on GPU CUDA Parallel Processing2626-849310.3991/ijoe.v17i11.24459https://doaj.org/article/434de85535374fddb44f85171047a20c2021-11-01T00:00:00Zhttps://online-journals.org/index.php/i-joe/article/view/24459https://doaj.org/toc/2626-8493The rapid development of computer technology has had a significant influence on advances in medical science. This development concerns segmenting medical images that can be used to help doctors diagnose patient diseases. The boundary between objects contained in an image is captured using the level set function. The equation of the level set function is solved numerically by combining the Lattice Boltzmann (LBM) method and fuzzy clustering. Parallel processing using a graphical processing unit (GPU) accelerates the execution of the segmentation process. The results showed that image segmentation with a relatively large size could be done quickly. The use of parallel programming with the GPU can accelerate up to 39.22 times compared to the speed of serial programming with the CPU. In addition, the comparisons with other research and benchmark data show consistent results.Ignasius Boli SubanSuyoto SuyotoPranowo PranowoInternational Association of Online Engineering (IAOE)articlelattice boltzmannfuzzy clusteringgpuComputer applications to medicine. Medical informaticsR858-859.7ENInternational Journal of Online and Biomedical Engineering, Vol 17, Iss 11, Pp 76-92 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	lattice boltzmann fuzzy clustering gpu Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	lattice boltzmann fuzzy clustering gpu Computer applications to medicine. Medical informatics R858-859.7 Ignasius Boli Suban Suyoto Suyoto Pranowo Pranowo Medical Image Segmentation Using a Combination of Lattice Boltzmann Method and Fuzzy Clustering Based on GPU CUDA Parallel Processing
description	The rapid development of computer technology has had a significant influence on advances in medical science. This development concerns segmenting medical images that can be used to help doctors diagnose patient diseases. The boundary between objects contained in an image is captured using the level set function. The equation of the level set function is solved numerically by combining the Lattice Boltzmann (LBM) method and fuzzy clustering. Parallel processing using a graphical processing unit (GPU) accelerates the execution of the segmentation process. The results showed that image segmentation with a relatively large size could be done quickly. The use of parallel programming with the GPU can accelerate up to 39.22 times compared to the speed of serial programming with the CPU. In addition, the comparisons with other research and benchmark data show consistent results.
format	article
author	Ignasius Boli Suban Suyoto Suyoto Pranowo Pranowo
author_facet	Ignasius Boli Suban Suyoto Suyoto Pranowo Pranowo
author_sort	Ignasius Boli Suban
title	Medical Image Segmentation Using a Combination of Lattice Boltzmann Method and Fuzzy Clustering Based on GPU CUDA Parallel Processing
title_short	Medical Image Segmentation Using a Combination of Lattice Boltzmann Method and Fuzzy Clustering Based on GPU CUDA Parallel Processing
title_full	Medical Image Segmentation Using a Combination of Lattice Boltzmann Method and Fuzzy Clustering Based on GPU CUDA Parallel Processing
title_fullStr	Medical Image Segmentation Using a Combination of Lattice Boltzmann Method and Fuzzy Clustering Based on GPU CUDA Parallel Processing
title_full_unstemmed	Medical Image Segmentation Using a Combination of Lattice Boltzmann Method and Fuzzy Clustering Based on GPU CUDA Parallel Processing
title_sort	medical image segmentation using a combination of lattice boltzmann method and fuzzy clustering based on gpu cuda parallel processing
publisher	International Association of Online Engineering (IAOE)
publishDate	2021
url	https://doaj.org/article/434de85535374fddb44f85171047a20c
work_keys_str_mv	AT ignasiusbolisuban medicalimagesegmentationusingacombinationoflatticeboltzmannmethodandfuzzyclusteringbasedongpucudaparallelprocessing AT suyotosuyoto medicalimagesegmentationusingacombinationoflatticeboltzmannmethodandfuzzyclusteringbasedongpucudaparallelprocessing AT pranowopranowo medicalimagesegmentationusingacombinationoflatticeboltzmannmethodandfuzzyclusteringbasedongpucudaparallelprocessing
_version_	1718426599500546048

Medical Image Segmentation Using a Combination of Lattice Boltzmann Method and Fuzzy Clustering Based on GPU CUDA Parallel Processing

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