Group Information Guided Smooth Independent Component Analysis Method for Multi-Subject fMRI Data Analysis

Group independent component analysis (ICA) has been extensively used to extract brain functional networks (FNs) and associated neuroimaging measures from multi-subject functional magnetic resonance imaging (fMRI) data. However, the inherent noise in fMRI data can adversely affect the performance of...

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Vydané v:	IEEE journal of biomedical and health informatics Ročník PP; s. 1 - 13
Hlavní autori:	Du, Yuhui, Huang, Chen, Calhoun, Vince D.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 18.07.2025
Predmet:	Accuracy Bioinformatics Biomarkers Brain functional network Data mining Functional magnetic resonance imaging Independent component analysis Multi-objective optimization Noise Optimization Reliability Smoothness Training
ISSN:	2168-2194, 2168-2208, 2168-2208
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