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  Impact of gradient non-linearities on B-tensor diffusion encoding

Paquette, M., Tax, C. M., Eichner, C., & Anwander, A. (2020). Impact of gradient non-linearities on B-tensor diffusion encoding. In Proceedings of the 28th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM).

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-D4AF-6 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-D4B0-3
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 Creators:
Paquette, Michael1, Author              
Tax, Chantal M.W. , 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: We investigate the effect of gradient non-linearities (GNL) on free gradient waveform used for B-tensor diffusion encoding. We show the magnitude of the GNL-bias for strong gradients of 300 mT/m. We derive a closed-form formula of the voxelwise B-tensor under GNL, independent of the choice of gradient waveform used to encode the B-tensor.

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 Dates: 2020-08-08
 Publication Status: Published online
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Title: Proceedings of the 28th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM)
Source Genre: Proceedings
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Pages: - Volume / Issue: 28 Sequence Number: 4412 Start / End Page: - Identifier: -