Multi-fiber reconstruction from DW-MRI using a continuous mixture of hyperspherical von mises-fisher distributions

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

Volumn 5636 LNCS, Issue , 2009, Pages 139-150

  Kumar, Ritwik ^a   Vemuri, Baba C ^a   Wang, Fei ^b   Syeda Mahmood, Tanveer ^b   Carney, Paul R ^c   Mareci, Thomas H ^a  

^a UNIVERSITY OF FLORIDA   (United States)

^b IBM ALMADEN RESEARCH CENTER   (United States)

^c UNIVERSITY OF FLORIDA COLLEGE OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLOSED-FORM EXPRESSION; COMPUTATIONAL ADVANTAGES; COMPUTATIONALLY EFFICIENT; CONTINUOUS MIXTURES; DETECTION ACCURACY; DIFFUSION-WEIGHTED MRI; HYPERSPHERICAL; IN-FIBER; KEY ISSUES; MIXTURE COMPONENTS; MR SIGNALS; RAT BRAIN; SINGLE VOXEL; STATE-OF-THE-ART METHODS; SYNTHETIC AND REAL DATA; VON MISES-FISHER DISTRIBUTION;

COMPUTATIONAL EFFICIENCY; COMPUTER SIMULATION; DATA PROCESSING; DIFFUSION; FIBERS; MEDICAL IMAGING; MIXTURES; REPAIR; SIGNAL PROCESSING;

MATHEMATICAL MODELS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BRAIN; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; DIFFUSION WEIGHTED IMAGING; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; MYELINATED NERVE; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL DISTRIBUTION; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING; ULTRASTRUCTURE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; CLUSTER ANALYSIS; COMPUTER SIMULATION; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NERVE FIBERS, MYELINATED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STATISTICAL DISTRIBUTIONS;

EID: 70349331412     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02498-6_12     Document Type: Conference Paper

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