Combining various types of classifiers and features extracted from magnetic resonance imaging data in schizophrenia recognition

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F15%3A00087443" target="_blank" >RIV/00216224:14110/15:00087443 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1016/j.pscychresns.2015.03.004" target="_blank" >http://dx.doi.org/10.1016/j.pscychresns.2015.03.004</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.pscychresns.2015.03.004" target="_blank" >10.1016/j.pscychresns.2015.03.004</a>

Result language

angličtina

Original language name

Combining various types of classifiers and features extracted from magnetic resonance imaging data in schizophrenia recognition

Original language description

We investigated a combination of three classification algorithms, namely the modified maximum uncertainty linear discriminant analysis (mMLDA), the centroid method, and the average linkage, with three types of features extracted from three-dimensional T1-weighted magnetic resonance (MR) brain images, specifically MR intensities, grey matter densities, and local deformations for distinguishing 49 first episode schizophrenia male patients from 49 healthy male subjects. The feature sets were reduced using intersubject principal component analysis before classification. By combining the classifiers, we were able to obtain slightly improved results when compared with single classifiers. The best classification performance (81.6% accuracy, 75.5% sensitivity, and 87.8% specificity) was significantly better than classification by chance.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

FH - Neurology, neuro-surgery, nuero-sciences

OECD FORD branch

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Project

<a href="/en/project/NT13359" target="_blank" >NT13359: Advanced Methods for Recognition of MR brain images for Computer Aided Diagnosis of Neuropsychiatric Disorders</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2015

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Psychiatry Research: Neuroimaging

ISSN

0925-4927

e-ISSN

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Volume of the periodical

232

Issue of the periodical within the volume

3

Country of publishing house

IE - IRELAND

Number of pages

13

Pages from-to

237-249

UT code for WoS article

000354552900006

EID of the result in the Scopus database

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