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Meeting Abstract

Gradient non-linearity correction for spherical mean diffusion imaging

MPS-Authors
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Paquette,  Michael
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Eichner,  Cornelius
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Anwander,  Alfred
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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http://indexsmart.mirasmart.com/ISMRM2019/PDFfiles/0550.html
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Citation

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).


Cite as: https://hdl.handle.net/21.11116/0000-0003-AC1E-B
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.