A Review on Parallel Medical Image Processing on GPU

An efficient implementation are necessary, as most medical imaging methods are computational expensive, and the amount of medical imaging data is growing .Graphic processing units (GPUs) can solve large data parallel problems at a higher speed than the traditional CPU, while being more affordab...

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Main Authors: Khor, Hui Liang, Liew, Siau-Chuin, Jasni, Mohamad Zain
Format: Conference or Workshop Item
Language:English
Published: IEEE 2015
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/10662/
http://umpir.ump.edu.my/id/eprint/10662/
http://umpir.ump.edu.my/id/eprint/10662/1/1570174065.pdf
id ump-10662
recordtype eprints
spelling ump-106622018-05-21T06:14:42Z http://umpir.ump.edu.my/id/eprint/10662/ A Review on Parallel Medical Image Processing on GPU Khor, Hui Liang Liew, Siau-Chuin Jasni, Mohamad Zain Q Science (General) QA76 Computer software An efficient implementation are necessary, as most medical imaging methods are computational expensive, and the amount of medical imaging data is growing .Graphic processing units (GPUs) can solve large data parallel problems at a higher speed than the traditional CPU, while being more affordable and energy efficient than distributed systems. This review investigates the use of GPUs to accelerate medical imaging methods. A set of criteria for efficient use of GPUs are defined. The review concludes that most medical image processing methods may benefit from GPU processing due to the methods’ data parallel structure and high thread count. However, factors such as synchronization, branch divergence and memory usage can limit the speedup. IEEE 2015-08 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/10662/1/1570174065.pdf Khor, Hui Liang and Liew, Siau-Chuin and Jasni, Mohamad Zain (2015) A Review on Parallel Medical Image Processing on GPU. In: IEEE 4th International Conference on Software Engineering and Computer Systems, 19-21 August 2015 , Kuantan, Pahang, Malaysia. pp. 45-48.. ISBN 978-1-4673-6722-6 http://dx.doi.org/10.1109/ICSECS.2015.7333121
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic Q Science (General)
QA76 Computer software
spellingShingle Q Science (General)
QA76 Computer software
Khor, Hui Liang
Liew, Siau-Chuin
Jasni, Mohamad Zain
A Review on Parallel Medical Image Processing on GPU
description An efficient implementation are necessary, as most medical imaging methods are computational expensive, and the amount of medical imaging data is growing .Graphic processing units (GPUs) can solve large data parallel problems at a higher speed than the traditional CPU, while being more affordable and energy efficient than distributed systems. This review investigates the use of GPUs to accelerate medical imaging methods. A set of criteria for efficient use of GPUs are defined. The review concludes that most medical image processing methods may benefit from GPU processing due to the methods’ data parallel structure and high thread count. However, factors such as synchronization, branch divergence and memory usage can limit the speedup.
format Conference or Workshop Item
author Khor, Hui Liang
Liew, Siau-Chuin
Jasni, Mohamad Zain
author_facet Khor, Hui Liang
Liew, Siau-Chuin
Jasni, Mohamad Zain
author_sort Khor, Hui Liang
title A Review on Parallel Medical Image Processing on GPU
title_short A Review on Parallel Medical Image Processing on GPU
title_full A Review on Parallel Medical Image Processing on GPU
title_fullStr A Review on Parallel Medical Image Processing on GPU
title_full_unstemmed A Review on Parallel Medical Image Processing on GPU
title_sort review on parallel medical image processing on gpu
publisher IEEE
publishDate 2015
url http://umpir.ump.edu.my/id/eprint/10662/
http://umpir.ump.edu.my/id/eprint/10662/
http://umpir.ump.edu.my/id/eprint/10662/1/1570174065.pdf
first_indexed 2023-09-18T22:10:31Z
last_indexed 2023-09-18T22:10:31Z
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