Model-free, regularized, fast, and robust analytical orientation distribution function estimation

  • Authors:

  • Jian Cheng;Aurobrata Ghosh;Rachid Deriche;Tianzi Jiang

  • Affiliations:

  • LIAMA, Institute of Automation, Chinese Academy of Sciences, China and INRIA Sophia Antipolis, Méditerranée, France;INRIA Sophia Antipolis, Méditerranée, France;INRIA Sophia Antipolis, Méditerranée, France;LIAMA, Institute of Automation, Chinese Academy of Sciences, China

  • Venue:
  • MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
  • Year:
  • 2010

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Abstract

High Angular Resolution Imaging (HARDI) can better explore the complex micro-structure of white matter compared to Diffusion Tensor Imaging (DTI). Orientation Distribution Function (ODF) in HARDI is used to describe the probability of the fiber direction. There are two type definitions of the ODF, which were respectively proposed in Q-Ball Imaging (QBI) and Diffusion Spectrum Imaging (DSI). Some analytical reconstructions methods have been proposed to estimate these two type of ODFs from single shell HARDI data. However they all have some assumptions and intrinsic modeling errors. In this article, we propose, almost without any assumption, a uniform analytical method to estimate these two ODFs from DWI signals in q space, which is based on Spherical Polar Fourier Expression (SPFE) of signals. The solution is analytical and is a linear transformation from the q-space signal to the ODF represented by Spherical Harmonics (SH). It can naturally combines the DWI signals in different Q-shells. Moreover It can avoid the intrinsic Funk-Radon Transform (FRT) blurring error in QBI and it does not need any assumption of the signals, such as the multiple tensor model and mono/multi-exponential decay. We validate our method using synthetic data, phantom data and real data. Our method works well in all experiments, especially for the data with low SNR, low anisotropy and non-exponential decay.