Unsupervised learning and mapping of brain fMRI signals based on hidden semi-Markov event sequence models

Lecture Notes in Computer Science

Volumn 2879, Issue PART 2, 2003, Pages 75-82

  Faisan, Sylvain ^a,b   Thoraval, Laurent ^a   Armspach, Jean Paul ^b   Heitz, Fabrice ^a  

^a Faculté de Médecine   (France)

^b CNRS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA PROCESSING; FORMAL LANGUAGES; HEURISTIC METHODS; IMAGING TECHNIQUES; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBABILITY; PROBLEM SOLVING; SIGNAL TO NOISE RATIO; BRAIN; BRAIN MAPPING; HIDDEN MARKOV MODELS; ITERATIVE METHODS; MAPPING; MEDICAL COMPUTING; MEDICAL IMAGING; NEURONS; SIGNAL SYSTEMS;

BRAIN MAPPING; LANGUAGE PROCESSING; LINEAR MODEL; SEMI-MARKOV EVENT SEQUENCE MODELS; ACROSS TIME; BRAIN ACTIVATION; FUNCTIONAL MRI (FMRI); NEURAL ACTIVITY; PRIOR KNOWLEDGE; TIME ALIGNMENT;

SIGNAL SYSTEMS; FUNCTIONAL NEUROIMAGING;

EID: 11244323933     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-39903-2_10     Document Type: Conference Paper

References (10)

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