Quantifying brain connectivity: A comparative tractography study

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 886-893

  Yo, Ting Shuo ^a   Anwander, Alfred ^a   Descoteaux, Maxime ^b   Fillard, Pierre ^b   Poupon, Cyril ^b   Knosche T R ^a  

^a MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

^b CEA SACLAY   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ANGULAR STRUCTURE; BRAIN AREAS; BRAIN CONNECTIVITY; BRAIN REGIONS; CONNECTED REGION; DATA SETS; DETERMINISTIC METHODS; DIFFUSION TENSOR; FIBER CROSSINGS; IN-DIFFUSION; PROBABILISTIC APPROACHES; REPRESENTATIVE SELECTION; SPHERICAL DECONVOLUTION; STATE-OF-THE-ART ALGORITHMS; STICK MODEL; TENSOR MODEL; TRACTOGRAPHY;

BRAIN MODELS; MAGNETIC RESONANCE IMAGING; MEDICAL COMPUTING; RESONANCE;

TENSORS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; CYTOLOGY; DIFFUSION TENSOR IMAGING; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; MYELINATED NERVE; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING; ULTRASTRUCTURE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; DIFFUSION TENSOR IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; NERVE FIBERS, MYELINATED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84863408240     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04268-3_109     Document Type: Conference Paper

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