title: Reliable Dual Tensor Model Estimation in Single and Crossing Fibers Based on Jeffreys Prior.
abstract: OBJECTIVE
  This paper presents and studies a framework for reliable modeling of diffusion MRI using a data-acquisition adaptive prior.
  
  
  METHODS
  Automated relevance determination estimates the mean of the posterior distribution of a rank-2 dual tensor model exploiting Jeffreys prior (JARD). This data-acquisition prior is based on the Fisher information matrix and enables the assessment whether two tensors are mandatory to describe the data. The method is compared to Maximum Likelihood Estimation (MLE) of the dual tensor model and to FSL's ball-and-stick approach.
  
  
  RESULTS
  Monte Carlo experiments demonstrated that JARD's volume fractions correlated well with the ground truth for single and crossing fiber configurations. In single fiber configurations JARD automatically reduced the volume fraction of one compartment to (almost) zero. The variance in fractional anisotropy (FA) of the main tensor component was thereby reduced compared to MLE. JARD and MLE gave a comparable outcome in data simulating crossing fibers. On brain data, JARD yielded a smaller spread in FA along the corpus callosum compared to MLE. Tract-based spatial statistics demonstrated a higher sensitivity in detecting age-related white matter atrophy using JARD compared to both MLE and the ball-and-stick approach.
  
  
  CONCLUSIONS
  The proposed framework offers accurate and precise estimation of diffusion properties in single and dual fiber regions.
authors.affiliation: Quantitative Imaging Group, Department of Imaging Physics, Delft University of Technology, 2628CJ Delft, The Netherlands.|Department of Radiology, Academic Medical Center Amsterdam, 1105AZ Amsterdam, The Netherlands.
authors.forename: Jianfei
authors.initials: J
authors.lastname: Yang
authors.affiliation: Quantitative Imaging Group, Department of Imaging Physics, Delft University of Technology, 2628CJ Delft, The Netherlands.|BIGR, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands.
authors.forename: Dirk H J
authors.initials: DH
authors.lastname: Poot
authors.affiliation: Department of Radiology, Academic Medical Center Amsterdam, 1105AZ Amsterdam, The Netherlands.
authors.forename: Matthan W A
authors.initials: MW
authors.lastname: Caan
authors.affiliation: Department of Radiology, Academic Medical Center Amsterdam, 1105AZ Amsterdam, The Netherlands.
authors.forename: Tanja
authors.initials: T
authors.lastname: Su
authors.affiliation: Department of Radiology, Academic Medical Center Amsterdam, 1105AZ Amsterdam, The Netherlands.
authors.forename: Charles B L M
authors.initials: CB
authors.lastname: Majoie
authors.affiliation: Quantitative Imaging Group, Department of Imaging Physics, Delft University of Technology, 2628CJ Delft, The Netherlands.
authors.forename: Lucas J
authors.initials: LJ
authors.lastname: van Vliet
authors.affiliation: Quantitative Imaging Group, Department of Imaging Physics, Delft University of Technology, 2628CJ Delft, The Netherlands.|Department of Radiology, Academic Medical Center Amsterdam, 1105AZ Amsterdam, The Netherlands.
authors.forename: Frans M
authors.initials: FM
authors.lastname: Vos
mesh_terms: D000368:Aged; D016880:Anisotropy; D001921:Brain / Q000000981:diagnostic imaging; D016022:Case-Control Studies; D038524:Diffusion Magnetic Resonance Imaging; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009010:Monte Carlo Method