Adjusting the neuroimaging statistical inferences for nonstationarity

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

Volumn 5761 LNCS, Issue PART 1, 2009, Pages 992-999

  Salimi Khorshidi, Gholamreza ^a   Smith, Stephen M ^a   Nichols, Thomas E ^a,b  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b GLAXOSMITHKLINE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ADJUSTMENT METHOD; CLUSTER SIZES; CLUSTER-BASED; CLUSTER-BASED METHODS; CLUSTER-SIZE DISTRIBUTION; FALSE POSITIVE; FALSE POSITIVE RATES; FREE CLUSTERS; NEURO-IMAGING; NEW APPROACHES; NON-STATIONARITIES; RANDOM FIELD THEORY; SMOOTH REGIONS; STATIONARITY; STATISTICAL INFERENCE;

MEDICAL COMPUTING;

RISK PERCEPTION;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BRAIN; BRAIN MAPPING; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STOCHASTIC PROCESSES;

EID: 84860400185     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04268-3_122     Document Type: Conference Paper

References (13)

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