Spherical tensor diffusion encoding with spectral specificity and isotropy

Motivation: Lack of spectral selectivity in spherical tensor diffusion encoding impairs the specificity of the measurement. Goal(s): The goal of this work was to design diffusion gradient waveforms yielding a spherical b-tensor with frequency-specific and isotropic spectral projections. Approach: Gradient waveform designs derived from oscillating gradient diffusion methodology were conceived by shifting and overlapping cosine-modulated trapezoidal oscillations along the three coordinate axes to achieve orthonormality of the b-tensor. Results: The proposed gradient waveforms achieved frequency-specific and isotropic diffusion encoding, permitting frequency-dependent diffusion measurements in the in vivo human brain in the same manner as is conventionally performed using multidirectional linear tensor diffusion encoding. Impact: The proposed diffusion gradient waveforms for spectrally specific and isotropic spherical tensor encoding offer selective frequency measurements that can isolate the signatures of time-dependent diffusion, thereby enabling the study of diffusion dispersion in the framework of tensor-valued encoding.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/5098
Citations
1
Primary Topic
Tensor decomposition and applications
Type
article
Field-Weighted Citation Impact
0.33
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article

Spherical tensor diffusion encoding with spectral specificity and isotropy

Franciszek Hennel, Eric Seth Michael, Klaas P. Pruessmann, Ru Jiang Hao
1 citations
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Tensor decomposition and applications
0.33
article

Spherical tensor diffusion encoding with spectral specificity and isotropy

Franciszek Hennel, Eric Seth Michael, Klaas P. Pruessmann, Ru Jiang Hao
article en
1 citations

Abstract

Motivation: Lack of spectral selectivity in spherical tensor diffusion encoding impairs the specificity of the measurement. Goal(s): The goal of this work was to design diffusion gradient waveforms yielding a spherical b-tensor with frequency-specific and isotropic spectral projections. Approach: Gradient waveform designs derived from oscillating gradient diffusion methodology were conceived by shifting and overlapping cosine-modulated trapezoidal oscillations along the three coordinate axes to achieve orthonormality of the b-tensor. Results: The proposed gradient waveforms achieved frequency-specific and isotropic diffusion encoding, permitting frequency-dependent diffusion measurements in the in vivo human brain in the same manner as is conventionally performed using multidirectional linear tensor diffusion encoding. Impact: The proposed diffusion gradient waveforms for spectrally specific and isotropic spherical tensor encoding offer selective frequency measurements that can isolate the signatures of time-dependent diffusion, thereby enabling the study of diffusion dispersion in the framework of tensor-valued encoding.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 47%
Tensor decomposition and applications
0.33
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Spherical tensor diffusion encoding with spectral specificity and isotropy — Franciszek Hennel, Eric Seth Michael, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2024) | TGRS Research Map | TGRS