A novel local PCA-based method for detecting activation signals in fMRI

Magnetic Resonance Imaging

Volumn 17, Issue 6, 1999, Pages 827-836

  Lai, Shang Hong ^a   Fang, Ming ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

Activation signal detection; Baseline drift correction; Functional magnetic resonance imaging (fMRI); Local principal component analysis (LPCA); Principal component analysis (PCA)

Indexed keywords

ALGORITHM; ARTICLE; BRAIN; CLUSTER ANALYSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SIGNAL DETECTION;

ALGORITHMS; ARTIFACTS; BRAIN; CLUSTER ANALYSIS; DATA INTERPRETATION, STATISTICAL; HUMANS; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 0033027443     PISSN: 0730725X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0730-725X(99)00038-7     Document Type: Article

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