Resolving complex fibre architecture by means of sparse spherical deconvolution in the presence of isotropic diffusion

Q. Zhou; O. Michailovich; Y. Rathi

doi:10.1117/12.2043103

21 March 2014 Resolving complex fibre architecture by means of sparse spherical deconvolution in the presence of isotropic diffusion

Q. Zhou, O. Michailovich, Y. Rathi

Author Affiliations +

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 903425 (2014) https://doi.org/10.1117/12.2043103
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

High angular resolution diffusion imaging (HARDI) improves upon more traditional diffusion tensor imaging (DTI) in its ability to resolve the orientations of crossing and branching neural fibre tracts. The HARDI signals are measured over a spherical shell in q-space, and are usually used as an input to q-ball imaging (QBI) which allows estimation of the diffusion orientation distribution functions (ODFs) associated with a given region-of interest. Unfortunately, the partial nature of single-shell sampling imposes limits on the estimation accuracy. As a result, the recovered ODFs may not possess sufficient resolution to reveal the orientations of fibre tracts which cross each other at acute angles. A possible solution to the problem of limited resolution of QBI is provided by means of spherical deconvolution, a particular instance of which is sparse deconvolution. However, while capable of yielding high-resolution reconstructions over spacial locations corresponding to white matter, such methods tend to become unstable when applied to anatomical regions with a substantial content of isotropic diffusion. To resolve this problem, a new deconvolution approach is proposed in this paper. Apart from being uniformly stable across the whole brain, the proposed method allows one to quantify the isotropic component of cerebral diffusion, which is known to be a useful diagnostic measure by itself.

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Q. Zhou, O. Michailovich, and Y. Rathi "Resolving complex fibre architecture by means of sparse spherical deconvolution in the presence of isotropic diffusion", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 903425 (21 March 2014); https://doi.org/10.1117/12.2043103

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