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  Gradient non-linearity correction for spherical mean diffusion imaging

Paquette, M., Eichner, C., & Anwander, A. (2019). Gradient non-linearity correction for spherical mean diffusion imaging. In Proceedings of the 27th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM).

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Paquette, Michael1, Author              
Eichner, Cornelius1, Author              
Anwander, Alfred1, Author              
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1Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              

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 Abstract: Gradient non-linearities are a significant source of errors in MRI systems with strong gradients. In the case of diffusion imaging, they induce spatial deviation of the b-vectors. The spherical mean methods in diffusion relies on the acquisition of spherical b-shell. To recover accurate spherical mean values, it is necessary to undistort the diffusion signal. Therefore, we evaluated three correction methods for gradient non-linearities using the Connectom gradient system as a showcase. We show how a simple heuristic can reduce the spherical mean errors by 20 folds.

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 Dates: 2019-05-11
 Publication Status: Published online
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Grant ID : PDF-502732-2017
Funding program : NSERC scholarship
Funding organization : Natural Sciences and Engineering Research Council of Canada (NSERC)

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Title: Proceedings of the 27th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM)
Source Genre: Proceedings
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Pages: - Volume / Issue: 27 Sequence Number: 0550 Start / End Page: - Identifier: -