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Titolo:
Comparison of two exploratory data analysis methods for fMRI: fuzzy clustering vs. principal component analysis
Autore:
Baumgartner, R; Ryner, L; Richter, W; Summers, R; Jarmasz, M; Somorjai, R;
Indirizzi:
Natl Res Council Canada, Inst Biodiagnost, Winnipeg, MB R3B 1Y6, Canada Natl Res Council Canada Winnipeg MB Canada R3B 1Y6 eg, MB R3B 1Y6, Canada
Titolo Testata:
MAGNETIC RESONANCE IMAGING
fascicolo: 1, volume: 18, anno: 2000,
pagine: 89 - 94
SICI:
0730-725X(200001)18:1<89:COTEDA>2.0.ZU;2-Y
Fonte:
ISI
Lingua:
ENG
Soggetto:
DYNAMICS;
Keywords:
functional MR imaging; principal component analysis; fuzzy clustering analysis;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Citazioni:
25
Recensione:
Indirizzi per estratti:
Indirizzo: Somorjai, R Natl Res Council Canada, Inst Biodiagnost, 435 Ellice Ave, Winnipeg, MB R3B 1Y6, Canada Natl Res Council Canada 435 Ellice Ave Winnipeg MB Canada R3B 1Y6
Citazione:
R. Baumgartner et al., "Comparison of two exploratory data analysis methods for fMRI: fuzzy clustering vs. principal component analysis", MAGN RES IM, 18(1), 2000, pp. 89-94

Abstract

Exploratory data-driven methods such as Fuzzy clustering analysis (FCA) and Principal component analysis (PCA) may be considered as hypothesis-generating procedures that are complementary to the hypothesis-led statistical inferential methods in functional magnetic resonance imaging (fMRI). Here, a comparison between FCA and PCA is presented in a systematic fMRI study, with MR data acquired under the null condition, i.e., no activation, with different noise contributions and simulated, varying "activation. " The contrast-to-noise (CNR) ratio ranged between 1-10. We found that if fMRI data are corrupted by scanner noise only, FCA and PCA show comparable performance. Inthe presence of other sources of signal variation (e.g., physiological noise), FCA outperforms PCA in the entire CNR range of interest in fMRI, particularly for low CNR values. The comparison method that we introduced may beused to assess other exploratory approaches such as independent component analysis or neural network-based techniques. Crown Copyright (C) 2000. Published by Elsevier Science Inc.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 18/01/21 alle ore 16:12:40