A novel sparse group Gaussian graphical model for functional connectivity estimation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7917 LNCS, Issue , 2013, Pages 256-267

  Ng, Bernard ^a,b   Varoquaux, Gaël ^a   Poline, Jean Baptiste ^a   Thirion, Bertrand ^a  

^a INRIA SACLAY   (France)

^b STANFORD UNIVERSITY   (United States)

Author keywords

brain connectivity; fMRI; Gaussian graphical model; regularized consensus optimization; sparse inverse covariance estimation

Indexed keywords

BRAIN CONNECTIVITY; CONNECTIVITY INFORMATION; FMRI; FUNCTIONAL CONNECTIVITY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; GAUSSIAN GRAPHICAL MODELS; INVERSE COVARIANCE; OPTIMIZATION PROBLEMS;

DATA PROCESSING; GAUSSIAN DISTRIBUTION; GRAPHIC METHODS; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; OPTIMIZATION;

ESTIMATION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BRAIN; BRAIN MAPPING; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; CONNECTOME; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NORMAL DISTRIBUTION; PHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; CONNECTOME; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NORMAL DISTRIBUTION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84897689015     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-38868-2_22     Document Type: Conference Paper

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