Group analysis of resting-state fMRI by hierarchical Markov random fields

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

Volumn 7512 LNCS, Issue , 2012, Pages 189-196

  Liu, Wei ^a   Awate, Suyash P ^a   Fletcher, P Thomas ^a  

^a UNIVERSITY OF UTAH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

K-MEANS CLUSTERING; MARKOV PROCESSES; MAXIMUM PRINCIPLE; MEDICAL COMPUTING; MEDICAL IMAGING;

CLUSTERING METHODS; EXPECTATION-MAXIMIZATION FRAMEWORKS; FUNCTIONAL NETWORK; MARKOV RANDOM FIELD MODEL; MARKOV RANDOM FIELDS; RESTING STATE FUNCTIONAL MRIS; RESTING-STATE FMRI; SEQUENTIAL APPROACH;

IMAGE SEGMENTATION;

ADOLESCENT; ALGORITHM; ARTICLE; BRAIN; BRAIN MAPPING; COMPUTER ASSISTED DIAGNOSIS; FEMALE; HUMAN; IMAGE ENHANCEMENT; MALE; METHODOLOGY; NERVE CELL NETWORK; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; PROBABILITY; REPRODUCIBILITY; REST; SENSITIVITY AND SPECIFICITY;

ADOLESCENT; ALGORITHMS; BRAIN; BRAIN MAPPING; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MARKOV CHAINS; NERVE NET; REPRODUCIBILITY OF RESULTS; REST; SENSITIVITY AND SPECIFICITY;

MLCS; MLOWN;

EID: 84872907967     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33454-2_24     Document Type: Conference Paper

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