Efficient brain MRI segmentation algorithm on TK1

Che Lun Hung; Chun Yuan Lin; Yuan Huai Wu; Hsiao Hsi Wang; Yu Chen Hu

doi:10.1109/CIT/IUCC/DASC/PICOM.2015.208

Efficient brain MRI segmentation algorithm on TK1

Che Lun Hung, Chun Yuan Lin, Yuan Huai Wu, Hsiao Hsi Wang, Yu Chen Hu

Institute of Biomedical Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

In the past decades, image processing technologies have been applied to process medical images. Usually, image segmentation is an important strategy. Fuzzy c-means clustering algorithm has been wildly used for segmentation of brain magnetic resonance image. In the paper, we implement a genetic Fuzzy c-means clustering algorithm based on embedded graphic process units system, NVIDIA TK1, to accelerate computation speed of time-consuming on segmenting brain magnetic resonance image. The experimental results show that the proposed algorithm not only can used to analyze such image on cheap device but also gains from the performance.

Original language	English
Title of host publication	Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
Editors	Luigi Atzori, Xiaolong Jin, Stephen Jarvis, Lei Liu, Ramon Aguero Calvo, Jia Hu, Geyong Min, Nektarios Georgalas, Yulei Wu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1395-1399
Number of pages	5
ISBN (Electronic)	9781509001545
DOIs	https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.208
State	Published - 22 Dec 2015
Event	15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 - Liverpool, United Kingdom Duration: 26 Oct 2015 → 28 Oct 2015

Publication series

Name	Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015

Conference

Conference	15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
Country/Territory	United Kingdom
City	Liverpool
Period	26/10/15 → 28/10/15

Keywords

Brain
Genetic Fuzzy c-means
GPU
Magnetic resonanace
Parallel processing
White matter

Access to Document

10.1109/CIT/IUCC/DASC/PICOM.2015.208

Cite this

Hung, C. L., Lin, C. Y., Wu, Y. H., Wang, H. H., & Hu, Y. C. (2015). Efficient brain MRI segmentation algorithm on TK1. In L. Atzori, X. Jin, S. Jarvis, L. Liu, R. A. Calvo, J. Hu, G. Min, N. Georgalas, & Y. Wu (Eds.), Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 (pp. 1395-1399). [7363252] (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.208

Hung, Che Lun ; Lin, Chun Yuan ; Wu, Yuan Huai et al. / Efficient brain MRI segmentation algorithm on TK1. Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015. editor / Luigi Atzori ; Xiaolong Jin ; Stephen Jarvis ; Lei Liu ; Ramon Aguero Calvo ; Jia Hu ; Geyong Min ; Nektarios Georgalas ; Yulei Wu. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1395-1399 (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015).

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title = "Efficient brain MRI segmentation algorithm on TK1",

abstract = "In the past decades, image processing technologies have been applied to process medical images. Usually, image segmentation is an important strategy. Fuzzy c-means clustering algorithm has been wildly used for segmentation of brain magnetic resonance image. In the paper, we implement a genetic Fuzzy c-means clustering algorithm based on embedded graphic process units system, NVIDIA TK1, to accelerate computation speed of time-consuming on segmenting brain magnetic resonance image. The experimental results show that the proposed algorithm not only can used to analyze such image on cheap device but also gains from the performance.",

keywords = "Brain, Genetic Fuzzy c-means, GPU, Magnetic resonanace, Parallel processing, White matter",

author = "Hung, {Che Lun} and Lin, {Chun Yuan} and Wu, {Yuan Huai} and Wang, {Hsiao Hsi} and Hu, {Yu Chen}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; null ; Conference date: 26-10-2015 Through 28-10-2015",

year = "2015",

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doi = "10.1109/CIT/IUCC/DASC/PICOM.2015.208",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1395--1399",

editor = "Luigi Atzori and Xiaolong Jin and Stephen Jarvis and Lei Liu and Calvo, {Ramon Aguero} and Jia Hu and Geyong Min and Nektarios Georgalas and Yulei Wu",

booktitle = "Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015",

address = "United States",

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Hung, CL, Lin, CY, Wu, YH, Wang, HH & Hu, YC 2015, Efficient brain MRI segmentation algorithm on TK1. in L Atzori, X Jin, S Jarvis, L Liu, RA Calvo, J Hu, G Min, N Georgalas & Y Wu (eds), Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015., 7363252, Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015, Institute of Electrical and Electronics Engineers Inc., pp. 1395-1399, 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015, Liverpool, United Kingdom, 26/10/15. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.208

Efficient brain MRI segmentation algorithm on TK1. / Hung, Che Lun; Lin, Chun Yuan; Wu, Yuan Huai et al.

Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015. ed. / Luigi Atzori; Xiaolong Jin; Stephen Jarvis; Lei Liu; Ramon Aguero Calvo; Jia Hu; Geyong Min; Nektarios Georgalas; Yulei Wu. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1395-1399 7363252 (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Efficient brain MRI segmentation algorithm on TK1

AU - Hung, Che Lun

AU - Lin, Chun Yuan

AU - Wu, Yuan Huai

AU - Wang, Hsiao Hsi

AU - Hu, Yu Chen

PY - 2015/12/22

Y1 - 2015/12/22

N2 - In the past decades, image processing technologies have been applied to process medical images. Usually, image segmentation is an important strategy. Fuzzy c-means clustering algorithm has been wildly used for segmentation of brain magnetic resonance image. In the paper, we implement a genetic Fuzzy c-means clustering algorithm based on embedded graphic process units system, NVIDIA TK1, to accelerate computation speed of time-consuming on segmenting brain magnetic resonance image. The experimental results show that the proposed algorithm not only can used to analyze such image on cheap device but also gains from the performance.

AB - In the past decades, image processing technologies have been applied to process medical images. Usually, image segmentation is an important strategy. Fuzzy c-means clustering algorithm has been wildly used for segmentation of brain magnetic resonance image. In the paper, we implement a genetic Fuzzy c-means clustering algorithm based on embedded graphic process units system, NVIDIA TK1, to accelerate computation speed of time-consuming on segmenting brain magnetic resonance image. The experimental results show that the proposed algorithm not only can used to analyze such image on cheap device but also gains from the performance.

KW - Brain

KW - Genetic Fuzzy c-means

KW - GPU

KW - Magnetic resonanace

KW - Parallel processing

KW - White matter

UR - http://www.scopus.com/inward/record.url?scp=84964298567&partnerID=8YFLogxK

U2 - 10.1109/CIT/IUCC/DASC/PICOM.2015.208

DO - 10.1109/CIT/IUCC/DASC/PICOM.2015.208

M3 - Conference contribution

AN - SCOPUS:84964298567

T3 - Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015

SP - 1395

EP - 1399

BT - Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015

A2 - Atzori, Luigi

A2 - Jin, Xiaolong

A2 - Jarvis, Stephen

A2 - Liu, Lei

A2 - Calvo, Ramon Aguero

A2 - Hu, Jia

A2 - Min, Geyong

A2 - Georgalas, Nektarios

A2 - Wu, Yulei

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 26 October 2015 through 28 October 2015

ER -

Hung CL, Lin CY, Wu YH, Wang HH, Hu YC. Efficient brain MRI segmentation algorithm on TK1. In Atzori L, Jin X, Jarvis S, Liu L, Calvo RA, Hu J, Min G, Georgalas N, Wu Y, editors, Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1395-1399. 7363252. (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015). doi: 10.1109/CIT/IUCC/DASC/PICOM.2015.208

Efficient brain MRI segmentation algorithm on TK1

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Keywords

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