Publications of F Glang

Poster (24)

61.
Poster
Loktyushin, A.; Herz, K.; Dang, N.; Glang, F.; Deshmane, A.; Weinmüller, F.; Doerfler, A.; Schölkopf, B.; Scheffler, K.; Zaiss, M.: MRzero: Automated invention of MRI sequences using supervised learning. 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021) (2021)
62.
Poster
Weinmüller, S.; Dang, H.; Loktyushin, A.; Glang, F.; Doerfler, A.; Maier, A.; Schölkopf, B.; Scheffler, K.; Zaiss, M.: MRzero sequence generation using analytic signal equations as forward model and neural network reconstruction for efficient auto-encoding. 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021) (2021)
63.
Poster
Glang, F.: CEST-Lasso: L1-regularized linear projection based CEST evaluation and feature selection for reduced acquisition time. 8. International Workshop on Chemical Exchange Saturation Transfer Imaging (CEST 2020) (2020)
64.
Poster
Glang, F.; Deshmane, A.; Prokudin, S.; Martin, F.; Herz, K.; Lindig, T.; Bender, B.; Scheffler, K.; Zaiss, M.: DeepCEST 3T: Robust neural network prediction of 3T CEST MRI parameters including uncertainty quantification. 2020 ISMRM & SMRT Virtual Conference & Exhibition (2020)
65.
Poster
Mueller, S.; Glang, F.; Scheffler, K.; Zaiss, M.: pH mapping of brain tissue by a deep neural network trained on 9.4T CEST MRI data: pH-deepCEST. 2020 ISMRM & SMRT Virtual Conference & Exhibition (2020)
66.
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)
67.
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)

Patent (1)

68.
Patent
Zaiss, M.; Glang, F.; Prokudin, S.; Scheffler, K.: Machine learning based processing of magnetic resonance data, including an uncertainty quantification. US 2022/0179026 A1 (2022)

Preprint (1)

69.
Preprint
West, D.; Glang, F.; Endres, J.; Leitão, D.; Zaiss, M.; Hajnal, J.; Malik, S.: MR sequence design using digital twins of non-idealized hardware. (submitted)
Go to Editor View