Cohort-level brain mapping: Learning cognitive atoms to single out specialized regions

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

Volumn 7917 LNCS, Issue , 2013, Pages 438-449

  Varoquaux, Gaël ^a,b,c   Schwartz, Yannick ^a,b   Pinel, Philippe ^b,c   Thirion, Bertrand ^a,b  

^a INRIA   (France)

^b CEA SACLAY   (France)

^c Cognitive Neuroimaging Unit ^*  (France)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN NETWORKS; COMPUTATIONAL COSTS; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NETWORK; LARGE DATASETS; MAPPING STRATEGY; MULTI-SUBJECT STUDIES; ON-LINE ALGORITHMS;

BRAIN MAPPING; DATA PROCESSING; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING;

BRAIN;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; BRAIN MAPPING; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NERVE CELL NETWORK; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; BRAIN MAPPING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; NERVE NET; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84901261854     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-38868-2_37     Document Type: Conference Paper

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