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Journal Article (2)

1.
Journal Article
Glang, F.; Deshmane, A.; Prokudin, S.; Martin, F.; Herz, K.; Lindig, T.; Bender, B.; Scheffler, K.; Zaiss, M.: DeepCEST 3T: Robust MRI parameter determination and uncertainty quantification with neural networks-application to CEST imaging of the human brain at 3. Magnetic Resonance in Medicine 84 (1), pp. 450 - 466 (2020)
2.
Journal Article
Zaiss, M.; Deshmane, A.; Schuppert, M.; Herz, K.; Glang, F.; Ehses, P.; Lindig, T.; Bender, B.; Ernemann, U.; Scheffler, K.: DeepCEST: 9.4 T Chemical exchange saturation transfer MRI contrast predicted from 3 T data – a proof of concept study. Magnetic Resonance in Medicine 81 (6), pp. 3901 - 3914 (2019)

Meeting Abstract (1)

3.
Meeting Abstract
Loktyushin, A.; Herz, K.; Glang, F.; Schölkopf, B.; Scheffler, K.; Zaiss, M.: MRI zero: Fully automated invention of MRI sequences using supervised learning. In Magnetic Resonance Materials in Physics, Biology and Medicine, 32 (Supplement 1), S09.06, pp. S119 - S120. 36th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB 2019), Rotterdam, The Netherlands, October 03, 2019 - October 05, 2019. No longer published by Elsevier, Amsterdam (2019)

Poster (2)

4.
Poster
Glang, F.; Deshmane, A.; Martin, F.; Herz, K.; Scheffler, K.; Zaiss, M.: Can a neural network predict B0 maps from uncorrected CEST-spectra? 27th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2019), Montréal, QC, Canada (2019)
5.
Poster
Zaiss, M.; Martin, F.; Glang, F.; Herz, K.; Deshmane, A.; Bender, B.; Lindig, T.; Scheffler, K.: deepCEST: 9.4 T spectral super resolution from 3 T CEST MRI data: optimization of network architectures. 27th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2019), Montréal, QC, Canada (2019)

Working Paper (1)

6.
Working Paper
Loktyushin, A.; Herz, K.; Dang, N.; Glang, F.; Deshmane, A.; Doerfler, A.; Schölkopf, B.; Scheffler, K.; Zaiss, M.: MRI zero: Fully automated invention of MRI sequences using supervised learning. (submitted)
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