Performance evaluation of nonnegative matrix factorization algorithms to estimate task-related neuronal activities from fMRI data

Nonnegative matrix factorization (NMF) is a blind source separation (BSS) algorithm which is based on the distinct constraint of nonnegativity of the estimated parameters as well as on the measured data. In this study, according to the potential feasibility of NMF for fMRI data, the four most popula...

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Vydáno v:	Magnetic resonance imaging Ročník 31; číslo 3; s. 466 - 476
Hlavní autoři:	Ding, Xiaoyu, Lee, Jong-Hwan, Lee, Seong-Whan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Netherlands Elsevier Inc 01.04.2013
Témata:	Algorithms Blind source separation (BSS) Brain - pathology Brain - physiopathology Brain Mapping - methods Cerebral Cortex - physiopathology Dementia - pathology Dementia - physiopathology Evoked Potentials Functional magnetic resonance imaging (fMRI) Humans Image Interpretation, Computer-Assisted - methods Magnetic Resonance Imaging - methods Nonnegative matrix factorization (NMF) Radiology Reproducibility of Results Sensitivity and Specificity Visuomotor task Visuomotor task Blind source separation (BSS) Functional magnetic resonance imaging (fMRI) Nonnegative matrix factorization (NMF)
ISSN:	0730-725X, 1873-5894, 1873-5894
On-line přístup:	Získat plný text
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