Probabilistic fiber tracking using particle filtering

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

Volumn 4792 LNCS, Issue PART 2, 2007, Pages 144-152

  Zhang, Fan ^a   Goodlett, Casey ^b   Hancock, Edwin ^a   Gerig, Guido ^b  

^a UNIVERSITY OF YORK   (United Kingdom)

^b UNIVERSITY OF NORTH CAROLINA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MAGNETIC RESONANCE IMAGING; NONLINEAR SYSTEMS;

GLOBAL TRACKING MODEL; NONLINEAR STATE SPACE MODEL; PARTICLE FILTERING; POTENTIAL FIBERS;

PROBABILISTIC LOGICS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; CYTOLOGY; DIFFUSION WEIGHTED IMAGING; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; MYELINATED NERVE; NERVE TRACT; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; THREE DIMENSIONAL IMAGING; ULTRASTRUCTURE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; CYTOLOGY; DATA INTERPRETATION, STATISTICAL; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; METHODS; NERVE FIBERS, MYELINATED; NEURAL PATHWAYS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; ULTRASTRUCTURE;

EID: 38349071910     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75759-7_18     Document Type: Conference Paper

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