Nonparametric Bayesian inference of the fiber orientation distribution from diffusion-weighted MR images

Medical Image Analysis

Volumn 16, Issue 4, 2012, Pages 876-888

  Kaden, Enrico ^a   Kruggel, Frithjof ^b  

^a UNIVERSITY OF LEIPZIG   (Germany)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Diffusion MR imaging; Dirichlet process mixture; Lebesgue decomposition; Reversible jump MCMC; Spherical deconvolution

Indexed keywords

DIRICHLET PROCESS MIXTURE; LEBESGUE DECOMPOSITION; MR IMAGING; REVERSIBLE JUMP MCMC; SPHERICAL DECONVOLUTION;

BAYESIAN NETWORKS; IMPULSE RESPONSE; INFERENCE ENGINES; INVERSE PROBLEMS; MAGNETIC RESONANCE IMAGING; TISSUE;

DIFFUSION;

ARTICLE; BAYES THEOREM; DIFFUSION WEIGHTED IMAGING; GEOMETRY; HUMAN; MONTE CARLO METHOD; NERVE FIBER; NONPARAMETRIC TEST; PRIORITY JOURNAL; PROBABILITY; STATISTICAL MODEL; WHITE MATTER;

ALGORITHMS; ANISOTROPY; BAYES THEOREM; BRAIN; DIFFUSION TENSOR IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; NERVE FIBERS, MYELINATED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84859428504     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2012.01.004     Document Type: Article

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