Christophe Schülke
Christophe Schülke
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Reference-less measurement of the transmission matrix of a highly scattering material using a DMD and phase retrieval techniques
A Drémeau, A Liutkus, D Martina, O Katz, C Schülke, F Krzakala, S Gigan, ...
Optics express 23 (9), 11898-11911, 2015
An adaptive intelligence algorithm for undersampled knee MRI reconstruction
N Pezzotti, S Yousefi, MS Elmahdy, JHF Van Gemert, C Schuelke, ...
IEEE Access 8, 204825-204838, 2020
Approximate message-passing with spatially coupled structured operators, with applications to compressed sensing and sparse superposition codes
J Barbier, C Schülke, F Krzakala
Journal of Statistical Mechanics: Theory and Experiment 2015 (5), P05013, 2015
Blind calibration in compressed sensing using message passing algorithms
C Schulke, F Caltagirone, F Krzakala, L Zdeborová
Advances in Neural Information Processing Systems 26, 2013
An adaptive intelligence algorithm for undersampled knee mri reconstruction: Application to the 2019 fastmri challenge
N Pezzotti, S Yousefi, MS Elmahdy, J Van Gemert, C Schülke, M Doneva, ...
arXiv preprint arXiv:2004.07339, 2020
Adaptive-CS-Net: FastMRI with adaptive intelligence
N Pezzotti, E de Weerdt, S Yousefi, MS Elmahdy, J van Gemert, ...
arXiv preprint arXiv:1912.12259, 2019
Multiple phases in modularity-based community detection
C Schülke, F Ricci-Tersenghi
Physical Review E 92 (4), 042804, 2015
Evaluation of the robustness of learned MR image reconstruction to systematic deviations between training and test data for the models from the fastMRI challenge
PM Johnson, G Jeong, K Hammernik, J Schlemper, C Qin, J Duan, ...
Machine Learning for Medical Image Reconstruction: 4th International …, 2021
Blind sensor calibration using approximate message passing
C Schülke, F Caltagirone, L Zdeborová
Journal of Statistical Mechanics: Theory and Experiment 2015 (11), P11013, 2015
Phase diagram of matrix compressed sensing
C Schülke, P Schniter, L Zdeborová
Physical Review E 94 (6), 062136, 2016
High-resolution free-breathing quantitative first-pass perfusion cardiac MR using dual-Echo Dixon with Spatio-temporal acceleration
J Tourais, CM Scannell, T Schneider, E Alskaf, R Crawley, F Bosio, ...
Frontiers in Cardiovascular Medicine 9, 884221, 2022
Statistical physics of linear and bilinear inference problems
C Schülke
arXiv preprint arXiv:1607.00675, 2016
High-Resolution Free-Breathing Quantitative Myocardial Perfusion MRI Using Multi-Echo Dixon
J Tourais, T Schneider, C Scannell, R Franks, J Sanchez-Gonzalez, ...
ISMRM, 2020
Statistical inference with probabilistic graphical models
A Drémeau, C Schülke, Y Xu, D Shah
arXiv preprint arXiv:1409.4928, 2014
Correction of magnetic resonance images using multiple magnetic resonance imaging system configurations
CMJ Schuelke, K Sommer, GR Duensing, P Boernert
US Patent App. 17/923,617, 2023
Medical data collection for machine learning
A Ewald, T Nielsen, K Sommer, I Waechter-Stehle, CMJ Schülke, ...
US Patent 11,669,636, 2023
Comparison of reconstruction methods for accelerated cardiac MR stress perfusion after physical stress with supine ergometer
C Schülke, S Roujol, M Foppa, EV Gervino, KV Kissinger, B Goddu, ...
Proceedings of the 21st Annual Meeting if ISMRM, Salt Lake City, Utah, USA, 1318, 2013
Motion artifact prediction during data acquisition
A Saalbach, S Weiss, K Sommer, C Schuelke, M Helle
US Patent 11,633,123, 2023
Motion Compensated CT Reconstruction of the Head
S Wild, R Bippus, T Koehler, C Schülke, A Tsanda, F Bergner, M Grass
2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC …, 2022
The effect of intra-scan motion on AI reconstructions in MRI
L Beljaards, N Pezzotti, C Schülke, MJP van Osch, M Staring
Medical Imaging with Deep Learning, 2022
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