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  NN-driven mapping of multiple diffusion metrics at high to ultra-high resolution using the bSSFP frequency profile

Birk, F., Glang, F., Loktyushin, A., Birkl, C., Ehses, P., Scheffler, K., et al. (2021). NN-driven mapping of multiple diffusion metrics at high to ultra-high resolution using the bSSFP frequency profile. In 23rd Annual Meeting of the German Chapter of the ISMRM (pp. S78-S81). Zürich, Switzerland: ETH Zürich.

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 Creators:
Birk, F1, 2, Author              
Glang, F1, 2, Author              
Loktyushin, A1, 2, Author              
Birkl, C, Author
Ehses, P, Author              
Scheffler, K1, 2, Author              
Heule, R1, 2, Author              
Affiliations:
1Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Asymmetries in the bSSFP fre-quency profile comprise rich information about microstructural tissue properties and white matter fiber orientation. A neural network-driven approach is presented to simultaneously map multiple diffusion metrics from phase-cy-cled bSSFP data acquired at 3T and 9.4T.

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 Dates: 2021-09
 Publication Status: Published online
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Title: 23rd Annual Meeting of the German Chapter of the ISMRM (DS ISMRM 2021)
Place of Event: Zürich, Switzerland
Start-/End Date: 2021-09-09 - 2021-09-10

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Title: 23rd Annual Meeting of the German Chapter of the ISMRM
Source Genre: Proceedings
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Publ. Info: Zürich, Switzerland : ETH Zürich
Pages: - Volume / Issue: - Sequence Number: V22 Start / End Page: S78 - S81 Identifier: -