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Reseach Article

Grammatical Swarm based Segmentation Methodology for Lesion Segmentation in Brain MRI

by Tapas Si, Arunava De, Anup Kumar Bhattacharjee
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 4
Year of Publication: 2015
Authors: Tapas Si, Arunava De, Anup Kumar Bhattacharjee

Tapas Si, Arunava De, Anup Kumar Bhattacharjee . Grammatical Swarm based Segmentation Methodology for Lesion Segmentation in Brain MRI. International Journal of Computer Applications. 121, 4 ( July 2015), 1-8. DOI=10.5120/21525-4481

@article{ 10.5120/21525-4481,
author = { Tapas Si, Arunava De, Anup Kumar Bhattacharjee },
title = { Grammatical Swarm based Segmentation Methodology for Lesion Segmentation in Brain MRI },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 4 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { },
doi = { 10.5120/21525-4481 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:07:32.540606+05:30
%A Tapas Si
%A Arunava De
%A Anup Kumar Bhattacharjee
%T Grammatical Swarm based Segmentation Methodology for Lesion Segmentation in Brain MRI
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 4
%P 1-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

This paper presents Grammatical Swarm based segmentation methodology for lesion detection in brain's magnetic resonance image. In the proposed methodology, images are denoised using median filter at the outset. Secondly, images are segmented using Grammatical Swarm based hard-clustering technique. Finally, lesions are extracted from the segmented images. The proposed methodology is applied on six Axial-T2 magnetic resonance images and compared with Particle Swarm Optimizer, K-Means and FCM based segmentation methods using quantitative performance measurement index. The experimental results show that the proposed methodology statistically outperforms other methods.

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Index Terms

Computer Science
Information Sciences


Brain Magnetic resonance image Lesion Segmentation Clustering Grammatical swarm Particle swarm optimizer