Bayesian Kernel methods for analysis of functional neuroimages

IEEE Transactions on Medical Imaging

Volumn 26, Issue 12, 2007, Pages 1613-1624

  Lukic, Ana S ^a,b,c   Wernick, Miles N ^a,b   Tzikas, Dimitris G ^d   Chen, Xu ^e   Likas, Aristidis ^a,d   Galatsanos, Nikolas R ^a,d   Yang, Yongyi ^a,b   Zhao, Fuqiang ^f   Strother, Stephen C ^a,e  

^a IEEE   (United States)

^b Illinois Institute of Technology   (United States)

^c Predictek Inc   (United States)

^d UNIVERSITY OF IOANNINA   (Greece)

^e ROTMAN RESEARCH INSTITUTE   (Canada)

^f UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

Author keywords

Functional neuroimaging; Kernel methods; Relevance vector machine (RVM); Reversible jump Markov chain Monte Carlo (RJMCMC)

Indexed keywords

FUNCTIONAL NEUROIMAGING; KERNEL METHODS; RELEVANCE VECTOR MACHINE (RVM); REVERSIBLE-JUMP MARKOV-CHAIN MONTE-CARLO (RJMCMC);

BAYESIAN NETWORKS; FUNCTIONAL ANALYSIS; MARKOV PROCESSES; NEUROLOGY; SUPPORT VECTOR MACHINES;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BRAIN; CELL MEMBRANE POTENTIAL; COMPUTER SIMULATION; MATHEMATICAL COMPUTING; METHODOLOGY; MONTE CARLO METHOD; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; POSITRON EMISSION TOMOGRAPHY; PROBABILITY; ROC CURVE; SCINTISCANNING; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STATISTICAL MODEL; STATISTICS; TIME;

ALGORITHMS; BAYES THEOREM; BRAIN; COMPUTER SIMULATION; LIKELIHOOD FUNCTIONS; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MARKOV CHAINS; MEMBRANE POTENTIALS; MONTE CARLO METHOD; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; POSITRON-EMISSION TOMOGRAPHY; ROC CURVE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; TIME FACTORS;

EID: 36549061438     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2007.896934     Document Type: Article

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