Reconstruction of the Orientation Distribution Function in Single and Multiple Shell Q-Ball Imaging within Constant Solid Angle

Abstract

Q-ball imaging (QBI) is a high angular resolution diffusion imaging (HARDI) technique which has been proven very successful in resolving multiple intravoxel fiber orientations in MR images. The standard computation of the orientation distribution function (ODF, the probability of diffusion in a given direction) from q-ball data uses linear radial projection, neglecting the change in the volume element along each direction. This results in spherical distributions that are different from the true ODFs. For instance, they are neither normalized nor as sharp as expected, and generally require post-processing, such as artificial sharpening or spherical deconvolution. In this paper, a new technique is proposed that, by considering the solid angle factor, uses the mathematically correct definition of the ODF and results in a dimensionless and normalized ODF expression. Our model is flexible enough so ODFs can either be estimated from single q-shell datasets, or exploit the greater information available from multiple q-shell acquisitions. We show that this can be achieved by using a more accurate multi-exponential model for the diffusion signal. The improved performance of the proposed method is demonstrated on artificial data and real HARDI volumes.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2009
Accession Number
ADA513251

Entities

People

  • Christophe Lenglet
  • Essa Yacoub
  • Guillermo Sapiro
  • Iman Aganj
  • Kamil Ugurbil
  • Noam Harel

Organizations

  • University of Minnesota

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Bessel Functions
  • Brain
  • Coefficients
  • Data Acquisition
  • Delta Functions
  • Distribution Functions
  • Equations
  • Fourier Analysis
  • Integrals
  • Magnetic Resonance
  • Mathematics
  • Neuroimaging
  • Orientation (Direction)
  • Probability
  • Three Dimensional

Fields of Study

  • Physics

Readers

  • Computer Vision.
  • Medical Imaging.
  • Regression Analysis.