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A texture-based method for classification of schizophrenia using fMRI data

Paper ID Volume ID Publish Year Pages File Format Full-Text
5224 352 2015 9 PDF Available
Title
A texture-based method for classification of schizophrenia using fMRI data
Abstract

This paper presents a texture-based method for classification of individuals into schizophrenia patient and healthy control groups based on their resting state functional magnetic resonance imaging (R-fMRI) data. In this research a combination of three different classifiers is proposed for classification of subjects into predefined groups. For all fMRI scans, the number of time points is reduced using principal component analysis (PCA) method, which projects data onto a new space. Then, independent component analysis (ICA) algorithm is used for estimation of the independent components (ICs). ICs are sorted based on their variance. For feature extraction a texture based operator called volume local binary patterns (VLBP) is applied on the estimated ICs. In order to obtain a set of features with large discrimination power, a two-sample t-test method is used. Finally, a test subject is classified into patient or control group using a combination of three different classifiers based on a majority vote method. The performance of the proposed method is evaluated using a leave-one-out cross validation method. Experimental results reveal that the proposed method has a very high accuracy.

Keywords
Schizophrenia; Functional magnetic resonance imaging; Independent component analysis; Volume local binary patterns; Histogram extraction; T-test
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biocybernetics and Biomedical Engineering - Volume 35, Issue 1, 2015, Pages 45–53
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us