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  MRzero with dAUTOMAP reconstruction: automated invention of MR acquisition and neural network reconstruction

Dang, H., Weinmüller, S., Loktyushin, A., Glang, F., Dörfler, A., Maier, A., et al. (2021). MRzero with dAUTOMAP reconstruction: automated invention of MR acquisition and neural network reconstruction. In 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021).

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 Creators:
Dang, HN, Author
Weinmüller, S, Author
Loktyushin, A1, 2, Author              
Glang, F1, 2, Author              
Dörfler, 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: We present an end-to-end optimized T1 mapping utilizing MRzero - a fully differentiable Bloch-equation-based MRI sequence invention framework. A convolutional neural network is employed for combined image reconstruction and parameter mapping. The pipeline performs a joint optimization of sequence parameters and neural network parameters to create a full autoencoder for T1 mapping. We demonstrate for in vivo measurements at 3T, that the CNN based reconstruction and T1 mapping outperformes a conventional reconstruction with pixelwise neural network based T1 quantification.

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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: 0333 Start / End Page: - Identifier: -