Literature DB >> 21232611

Estimation of fiber orientation and spin density distribution by diffusion deconvolution.

Fang-Cheng Yeh1, Van Jay Wedeen, Wen-Yih Isaac Tseng.   

Abstract

A diffusion deconvolution method is proposed to apply deconvolution to the diffusion orientation distribution function (dODF) and calculate the fiber orientation distribution function (fODF), which is defined as the orientation distribution of the fiber spin density. The dODF can be obtained from q-space imaging methods such as q-ball imaging (QBI), diffusion spectrum imaging (DSI), and generalized q-sampling imaging (GQI), and thus the method can be applied to various diffusion sampling schemes. A phantom study was conducted to compare the angular resolution of the fODF with the dODF, and the in vivo datasets were acquired using single-shell, two-shell, and grid sampling schemes, which were then reconstructed by QBI, GQI, and DSI, respectively. The phantom study showed that the fODF significantly improved the angular resolution over the dODF at 45- and 60-degree crossing angles. The in vivo study showed consistent fODF regardless of the applied sampling schemes and reconstruction methods, and the ability to resolve crossing fibers was improved in reduced sampling condition. The fiber spin density obtained from deconvolution showed a higher contrast-to-noise ratio than the fractional anisotropy (FA) mapping, and further application on tractography showed that the fiber spin density can be used to determine the termination of fiber tracts. In conclusion, the proposed deconvolution method is generally applicable to different q-space imaging methods. The calculated fODF improves the angular resolution and also provides a quantitative index of fiber spin density to refine fiber tracking.
Copyright © 2011 Elsevier Inc. All rights reserved.

Mesh:

Year:  2011        PMID: 21232611     DOI: 10.1016/j.neuroimage.2010.11.087

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


  62 in total

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5.  Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity.

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6.  Network Controllability in the Inferior Frontal Gyrus Relates to Controlled Language Variability and Susceptibility to TMS.

Authors:  John D Medaglia; Denise Y Harvey; Nicole White; Apoorva Kelkar; Jared Zimmerman; Danielle S Bassett; Roy H Hamilton
Journal:  J Neurosci       Date:  2018-06-08       Impact factor: 6.167

7.  Driving the brain towards creativity and intelligence: A network control theory analysis.

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8.  DTI template-based estimation of cardiac fiber orientations from 3D ultrasound.

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Journal:  Med Phys       Date:  2015-06       Impact factor: 4.071

9.  [Diffusion-weighted imaging and diffusion tensor imaging in preoperative diagnostics].

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Journal:  Neuroimage       Date:  2013-04-13       Impact factor: 6.556

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