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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: https://hdl.handle.net/21.11116/0000-0006-D4AF-6 Version Permalink: https://hdl.handle.net/21.11116/0000-000B-932D-D
Genre: Conference Paper

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http://indexsmart.mirasmart.com/ISMRM2020/PDFfiles/4412.html (Any fulltext)
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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: -