A Riemannian framework for orientation distribution function computing

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 911-918

  Cheng, Jian ^a,b   Ghosh, Aurobrata ^b   Jiang, Tianzi ^a   Deriche, Rachid ^b  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b INRIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CLOSED FORM; COMPLEX MICROSTRUCTURES; DIFFUSION TENSOR IMAGING; EUCLIDEAN; EUCLIDEAN SPACES; EXPONENTIAL MAP; FIBER DIRECTION; FISHER INFORMATION METRIC; GEODESIC DISTANCES; GEOMETRIC ANISOTROPY; HIGH ANGULAR RESOLUTIONS; INFORMATION GEOMETRY; LAGRANGE INTERPOLATIONS; LOG-EUCLIDEAN FRAMEWORK; MODEL FREE; ORIENTATION DISTRIBUTION FUNCTION; ORTHONORMAL BASIS; PROBABILITY DENSITIES; PROBABILITY DENSITY FUNCTION (PDF); RENYI ENTROPY; RIEMANNIAN FRAMEWORK; SCALAR MEASUREMENTS; SPARSE REPRESENTATION; STATE OF THE ART; SYNTHETIC AND REAL DATA; THEORETICAL RESULT; WHITE MATTER;

ARTS COMPUTING; DISTRIBUTION FUNCTIONS; FISHER INFORMATION MATRIX; GEODESY; GEOMETRY; MEDICAL COMPUTING; PROBABILITY; TENSORS;

PROBABILITY DENSITY FUNCTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; 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: 84860671386     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04268-3_112     Document Type: Conference Paper

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