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Classification of Brain MRI using Wavelet Decomposition and SVM

by Pravada Deshmukh, P. S. Malge
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 154 - Number 5
Year of Publication: 2016
Authors: Pravada Deshmukh, P. S. Malge
10.5120/ijca2016912140

Pravada Deshmukh, P. S. Malge . Classification of Brain MRI using Wavelet Decomposition and SVM. International Journal of Computer Applications. 154, 5 ( Nov 2016), 29-33. DOI=10.5120/ijca2016912140

@article{ 10.5120/ijca2016912140,
author = { Pravada Deshmukh, P. S. Malge },
title = { Classification of Brain MRI using Wavelet Decomposition and SVM },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2016 },
volume = { 154 },
number = { 5 },
month = { Nov },
year = { 2016 },
issn = { 0975-8887 },
pages = { 29-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume154/number5/26489-2016912140/ },
doi = { 10.5120/ijca2016912140 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:59:26.595050+05:30
%A Pravada Deshmukh
%A P. S. Malge
%T Classification of Brain MRI using Wavelet Decomposition and SVM
%J International Journal of Computer Applications
%@ 0975-8887
%V 154
%N 5
%P 29-33
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automated classification of brain MRI is important for the analysis of tumor. In this paper brain MRI are taken for the classification and detection of tumor .It consists of four stages, discrete wavelet transform (DWT), texture feature extraction, Classification by support vector machine and last segmentation. Due to the structure of the tumor cells, its detection became a challenging problem. Segmentation is used to extract tumor region in brain, which is carried out by fuzzy c-means clustering algorithm. The features are extracted from horizontal (LH) and vertical (HL) sub bands of the wavelet transform.The system gives better performance as compared to LL sub band because LH and HL sub bands can effectively encode the selective features of normal and abnormal images.Based on standard methods the system was evaluated and validated

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Index Terms

Computer Science
Information Sciences

Keywords

MRI DWT texture feature SVM segmentation

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