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  MRzero sequence generation using analytic signal equations as forward model and neural network reconstruction for efficient auto-encoding

Weinmüller, S., Dang, H., Loktyushin, A., Glang, F., Doerfler, A., Maier, A., et al. (2021). MRzero sequence generation using analytic signal equations as forward model and neural network reconstruction for efficient auto-encoding. Poster presented at 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021).

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Item Permalink: https://hdl.handle.net/21.11116/0000-0008-8693-A Version Permalink: https://hdl.handle.net/21.11116/0000-0008-EF14-5
Genre: Poster

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https://www.ismrm.org/21/program-files/TeaserSlides/TeasersPresentations/1761-Teaser.html (Publisher version)
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 Creators:
Weinmüller, S, Author
Dang, HN, Author
Loktyushin, A1, 2, Author           
Glang, F1, 2, Author           
Doerfler, A, Author
Maier, A, Author
Schölkopf, B3, Author           
Scheffler, K1, 2, Author           
Zaiss, M1, 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              
3Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

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 Abstract: MRzero is a fully differentiable Bloch-equation-based MRI sequence invention framework. Instead of using time-consuming average-isochromat-based Bloch simulations, analytic signal equations are used as alternative forward differentiable MR scan simulation method. Neural network reconstruction is used for efficient auto-encoding. The joint optimization of sequence and NN parameters for B1 and T1 mapping can be performed 2 to 3 orders of magnitude faster then in previous MRzero approaches. The optimized sequence is tested by measurements in vivo at 3T and compared to a standard inversion recovery. High quality B1 and T1 maps are provided with less total acquisition time and energy deposition.

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 Dates: 2021-05
 Publication Status: Published online
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Title: 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021)
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Start-/End Date: 2021-05-15 - 2021-05-20

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Title: 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 1761 Start / End Page: - Identifier: -