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

• Autorzy: Pouyan A. A. , Shahamat H.

Identyfikatory

DOI

10.1016/j.bbe.2014.08.001

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

schizophrenia; functional magnetic resonance imaging; independent component analysis; volume local binary patterns; histogram extraction; t-test

PL

schizofrenia; funkcjonalny rezonans magnetyczny; analiza składowych niezależnych; lokalne wzorce binarne

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2015
• Tom: Vol. 35, no. 1
• Strony: 45--53
• Opis fizyczny: Bibliogr. 34 poz., rys., tab., wykr.

Twórcy

autor

Pouyan A. A.

• Department of Computer Engineering and Information Technology, Shahrood University of Technology, No. 316, Daneshgah Ave., Shahrood 3619995161, Semnan, Iran

autor

Shahamat H.

• Department of Computer Engineering and Information Technology, Shahrood University of Technology, No. 316, Daneshgah Ave., Shahrood 3619995161, Semnan, Iran

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