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Accuracy based Comparison of Three Brain Extraction Algorithms

by Gayatri Mirajkar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Number 18
Year of Publication: 2012
Authors: Gayatri Mirajkar
10.5120/7731-1232

Gayatri Mirajkar . Accuracy based Comparison of Three Brain Extraction Algorithms. International Journal of Computer Applications. 49, 18 ( July 2012), 45-57. DOI=10.5120/7731-1232

@article{ 10.5120/7731-1232,
author = { Gayatri Mirajkar },
title = { Accuracy based Comparison of Three Brain Extraction Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 49 },
number = { 18 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 45-57 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume49/number18/7731-1232/ },
doi = { 10.5120/7731-1232 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:46:36.713671+05:30
%A Gayatri Mirajkar
%T Accuracy based Comparison of Three Brain Extraction Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 18
%P 45-57
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Skull stripping is an important image processing step in many neuroimaging studies. In this paper, a comparison of three brain extraction algorithms is done, namely Brain Surface Extractor (BSE), skull stripping algorithm using Geodesic Active Contour (GAC), and skull stripping using active contours without edges. The comparison is done with respect to accuracy of the three algorithms. The results provided by the three algorithms are compared against the processed results available in the OASIS dataset. A comparison of the three algorithms shows that BSE provides the best results with respect to the percentage of non-brain matter contained in the final segmented output. The algorithm using GAC produces a conservative result containing some amount of non-brain matter that can be removed using morphological operator. The algorithm using active contours without edges produces segmentation results containing some amount of brain matter removed from the result. This is mainly due to the sensitivity of the active contour to intensity values in the sulci present in the brain magnetic resonance image.

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Index Terms

Computer Science
Information Sciences

Keywords

Magnetic resonance imaging skull stripping active contours geodesic active contours level sets

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