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Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

Volume 5762 of the series Lecture Notes in Computer Science pp 423-431

Multiple Q-Shell ODF Reconstruction in Q-Ball Imaging

  • Iman AganjAffiliated withDepartment of Electrical and Computer Engineering, University of Minnesota
  • , Christophe LengletAffiliated withDepartment of Electrical and Computer Engineering, University of MinnesotaCenter for Magnetic Resonance Research, University of Minnesota
  • , Guillermo SapiroAffiliated withDepartment of Electrical and Computer Engineering, University of Minnesota
  • , Essa YacoubAffiliated withCenter for Magnetic Resonance Research, University of Minnesota
  • , Kamil UgurbilAffiliated withCenter for Magnetic Resonance Research, University of Minnesota
  • , Noam HarelAffiliated withCenter for Magnetic Resonance Research, University of Minnesota

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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 uses linear radial projection, neglecting the change in the volume element along the ray, thereby resulting in distributions different from the true ODFs. A new technique has been recently 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 from a single q-shell. In this paper, we extend this technique in order to exploit HARDI data from multiple q-shells. We consider the more flexible multi-exponential model for the diffusion signal, and show how to efficiently compute the ODFs in constant solid angle. We describe our method and demonstrate its improved performance on both artificial and real HARDI data.