Literature DB >> 26432187

Fiber ball imaging.

Jens H Jensen1, G Russell Glenn2, Joseph A Helpern2.   

Abstract

By modeling axons as thin cylinders, it is shown that the inverse Funk transform of the diffusion MRI (dMRI) signal intensity obtained on a spherical shell in q-space gives an estimate for a fiber orientation density function (fODF), where the accuracy improves with increasing b-value provided the signal-to-noise ratio is sufficient. The method is similar to q-ball imaging, except that the Funk transform of q-ball imaging is replaced by its inverse. We call this new approach fiber ball imaging. The fiber ball method is demonstrated for healthy human brain, and fODF estimates are compared to diffusion orientation distribution function (dODF) approximations obtained with q-ball imaging. The fODFs are seen to have sharper features than the dODFs, reflecting an enhancement of the higher degree angular frequencies. The inverse Funk transform of the dMRI signal intensity data provides a simple and direct method of estimating a fODF. In addition, fiber ball imaging leads to an estimate for the ratio of the fraction of MRI visible water confined to the intra-axonal space divided by the square root of the intra-axonal diffusivity. This technique may be useful for white matter fiber tractography, as well as other types of microstructural modeling of brain tissue.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Brain; Diffusion MRI; Fiber orientation density function; Funk transform; High-angular-resolution diffusion imaging; Q-ball imaging

Mesh:

Year:  2015        PMID: 26432187      PMCID: PMC4651772          DOI: 10.1016/j.neuroimage.2015.09.049

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  42 in total

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5.  High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity.

Authors:  David S Tuch; Timothy G Reese; Mette R Wiegell; Nikos Makris; John W Belliveau; Van J Wedeen
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7.  Compartment models of the diffusion MR signal in brain white matter: a taxonomy and comparison.

Authors:  Eleftheria Panagiotaki; Torben Schneider; Bernard Siow; Matt G Hall; Mark F Lythgoe; Daniel C Alexander
Journal:  Neuroimage       Date:  2011-10-07       Impact factor: 6.556

8.  The Rician distribution of noisy MRI data.

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Journal:  Magn Reson Med       Date:  1995-12       Impact factor: 4.668

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Authors:  R M Henkelman
Journal:  Med Phys       Date:  1985 Mar-Apr       Impact factor: 4.071

10.  On the nature of the NAA diffusion attenuated MR signal in the central nervous system.

Authors:  Christopher D Kroenke; Joseph J H Ackerman; Dmitriy A Yablonskiy
Journal:  Magn Reson Med       Date:  2004-11       Impact factor: 4.668

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  31 in total

1.  Evaluating kurtosis-based diffusion MRI tissue models for white matter with fiber ball imaging.

Authors:  Jens H Jensen; Emilie T McKinnon; G Russell Glenn; Joseph A Helpern
Journal:  NMR Biomed       Date:  2017-01-13       Impact factor: 4.044

2.  Comparison of NODDI and spherical mean signal for measuring intra-neurite volume fraction.

Authors:  Hua Li; Rahul Nikam; Vinay Kandula; Ho Ming Chow; Arabinda K Choudhary
Journal:  Magn Reson Imaging       Date:  2018-11-26       Impact factor: 2.546

3.  Linking spherical mean diffusion weighted signal with intra-axonal volume fraction.

Authors:  Hua Li; Ho Ming Chow; Diane C Chugani; Harry T Chugani
Journal:  Magn Reson Imaging       Date:  2018-11-12       Impact factor: 2.546

4.  Dependence on b-value of the direction-averaged diffusion-weighted imaging signal in brain.

Authors:  Emilie T McKinnon; Jens H Jensen; G Russell Glenn; Joseph A Helpern
Journal:  Magn Reson Imaging       Date:  2016-10-27       Impact factor: 2.546

5.  Diffusion time dependence of microstructural parameters in fixed spinal cord.

Authors:  Sune Nørhøj Jespersen; Jonas Lynge Olesen; Brian Hansen; Noam Shemesh
Journal:  Neuroimage       Date:  2017-08-14       Impact factor: 6.556

6.  Estimating fiber orientation distribution from diffusion MRI with spherical needlets.

Authors:  Hao Yan; Owen Carmichael; Debashis Paul; Jie Peng
Journal:  Med Image Anal       Date:  2018-02-08       Impact factor: 8.545

Review 7.  Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation.

Authors:  Dmitry S Novikov; Els Fieremans; Sune N Jespersen; Valerij G Kiselev
Journal:  NMR Biomed       Date:  2018-10-15       Impact factor: 4.044

8.  TE dependent Diffusion Imaging (TEdDI) distinguishes between compartmental T2 relaxation times.

Authors:  Jelle Veraart; Dmitry S Novikov; Els Fieremans
Journal:  Neuroimage       Date:  2017-09-19       Impact factor: 6.556

9.  Rotationally-invariant mapping of scalar and orientational metrics of neuronal microstructure with diffusion MRI.

Authors:  Dmitry S Novikov; Jelle Veraart; Ileana O Jelescu; Els Fieremans
Journal:  Neuroimage       Date:  2018-03-12       Impact factor: 6.556

10.  Mapping the Orientation of White Matter Fiber Bundles: A Comparative Study of Diffusion Tensor Imaging, Diffusional Kurtosis Imaging, and Diffusion Spectrum Imaging.

Authors:  G R Glenn; L-W Kuo; Y-P Chao; C-Y Lee; J A Helpern; J H Jensen
Journal:  AJNR Am J Neuroradiol       Date:  2016-03-03       Impact factor: 3.825

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