Fixed-point algorithms for constrained ICA and their applications in fMRI data analysis

Magnetic Resonance Imaging

Volumn 29, Issue 9, 2011, Pages 1288-1303

  Wang, Ze ^a,b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Augmented Lagrangian; Constrained independent component analysis; Fixed point iteration; FMRI; General linear model; Independent component analysis; Newton like gradient

Indexed keywords

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; CONSTRAINED INDEPENDENT COMPONENT ANALYSIS; CONTROLLED STUDY; DATA ANALYSIS; FIXED POINT ALGORITHM; FUNCTIONAL MAGNETIC RESONANCE IMAGING; IMAGE ANALYSIS; INDEPENDENT COMPONENT ANALYSIS; INTERMETHOD COMPARISON; LEARNING; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; SENSORIMOTOR FUNCTION; SIGNAL NOISE RATIO; STATISTICAL MODEL; TASK PERFORMANCE;

ALGORITHMS; AREA UNDER CURVE; BRAIN; BRAIN MAPPING; HUMANS; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; MULTIVARIATE ANALYSIS; NORMAL DISTRIBUTION; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; ROC CURVE; SIGNAL PROCESSING, COMPUTER-ASSISTED; SOFTWARE;

EID: 80054780149     PISSN: 0730725X     EISSN: 18735894     Source Type: Journal    
DOI: 10.1016/j.mri.2011.07.017     Document Type: Article

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