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Enhancing the Efficiency of Parallel Genetic Algorithms for Medical Image Processing with Hadoop

by D. Peter Augustine
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 108 - Number 17
Year of Publication: 2014
Authors: D. Peter Augustine
10.5120/19002-0483

D. Peter Augustine . Enhancing the Efficiency of Parallel Genetic Algorithms for Medical Image Processing with Hadoop. International Journal of Computer Applications. 108, 17 ( December 2014), 11-16. DOI=10.5120/19002-0483

@article{ 10.5120/19002-0483,
author = { D. Peter Augustine },
title = { Enhancing the Efficiency of Parallel Genetic Algorithms for Medical Image Processing with Hadoop },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 108 },
number = { 17 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 11-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume108/number17/19002-0483/ },
doi = { 10.5120/19002-0483 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:43:13.426168+05:30
%A D. Peter Augustine
%T Enhancing the Efficiency of Parallel Genetic Algorithms for Medical Image Processing with Hadoop
%J International Journal of Computer Applications
%@ 0975-8887
%V 108
%N 17
%P 11-16
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, there is in-depth analysis of the parallel genetic algorithms used for segmentation of brain images and how their efficiency varies in the cloud setup with Hadoop. Since the current health care industry is moving towards the utmost usage of cloud to make the data available round the clock for the analysis, it is mandatory that the efficiency of the analysis also to be enhanced to produce the accurate result. Here, the focus is on the study of medical image processing that too narrowed down to the brain images with the help of parallel genetic algorithms in the cloud environment. The study aims to help the researchers to augment the competence of the algorithm when it functions in the remote cloud setup.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Efficiency of parallel genetic algorithms Image processing in cloud environment Brain Image processing Hdoop's Map Reduce.

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