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Christopher Syben
Christopher Syben
Scientist, Siemens Healthcare GmbH
Verifierad e-postadress på fau.de
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A gentle introduction to deep learning in medical image processing
A Maier, C Syben, T Lasser, C Riess
Zeitschrift für Medizinische Physik 29 (2), 86-101, 2019
5642019
Learning with known operators reduces maximum error bounds
AK Maier, C Syben, B Stimpel, T Würfl, M Hoffmann, F Schebesch, W Fu, ...
Nature machine intelligence 1 (8), 373-380, 2019
1722019
PYRO‐NN: Python reconstruction operators in neural networks
C Syben, M Michen, B Stimpel, S Seitz, S Ploner, AK Maier
Medical physics 46 (11), 5110-5115, 2019
672019
Precision learning: towards use of known operators in neural networks
A Maier, F Schebesch, C Syben, T Würfl, S Steidl, JH Choi, R Fahrig
2018 24th International Conference on Pattern Recognition (ICPR), 183-188, 2018
602018
Deep learning-based patient re-identification is able to exploit the biometric nature of medical chest X-ray data
K Packhäuser, S Gündel, N Münster, C Syben, V Christlein, A Maier
Scientific Reports 12 (1), 14851, 2022
352022
Multi-modal deep guided filtering for comprehensible medical image processing
B Stimpel, C Syben, F Schirrmacher, P Hoelter, A Dörfler, A Maier
IEEE transactions on medical imaging 39 (5), 1703-1711, 2019
312019
Detecting anatomical landmarks for motion estimation in weight-bearing imaging of knees
B Bier, K Aschoff, C Syben, M Unberath, M Levenston, G Gold, R Fahrig, ...
Machine Learning for Medical Image Reconstruction: First International …, 2018
312018
Precision learning: reconstruction filter kernel discretization
C Syben, B Stimpel, K Breininger, T Würfl, R Fahrig, A Dörfler, A Maier
arXiv preprint arXiv:1710.06287, 2017
282017
Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks.
E Hoppe, F Thamm, G Körzdörfer, C Syben, F Schirrmacher, M Nittka, ...
GMDS, 126-133, 2019
262019
Is medical chest X-ray data anonymous?
K Packhäuser, S Gündel, N Münster, C Syben, V Christlein, A Maier
252021
RinQ fingerprinting: recurrence-informed quantile networks for magnetic resonance fingerprinting
E Hoppe, F Thamm, G Körzdörfer, C Syben, F Schirrmacher, M Nittka, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2019
252019
Deriving neural network architectures using precision learning: Parallel-to-fan beam conversion
C Syben, B Stimpel, J Lommen, T Würfl, A Dörfler, A Maier
Pattern Recognition: 40th German Conference, GCPR 2018, Stuttgart, Germany …, 2019
242019
Age estimation on panoramic dental X-ray images using deep learning
S Wallraff, S Vesal, C Syben, R Lutz, A Maier
Bildverarbeitung für die Medizin 2021: Proceedings, German Workshop on …, 2021
192021
MR to X-ray projection image synthesis
B Stimpel, C Syben, T Würfl, K Mentl, A Dörfler, A Maier
arXiv preprint arXiv:1710.07498, 2017
182017
Maximum likelihood estimation of head motion using epipolar consistency
A Preuhs, N Ravikumar, M Manhart, B Stimpel, E Hoppe, C Syben, ...
Bildverarbeitung für die Medizin 2019: Algorithmen–Systeme–Anwendungen …, 2019
172019
Cephalogram synthesis and landmark detection in dental cone-beam CT systems
Y Huang, F Fan, C Syben, P Roser, L Mill, A Maier
Medical Image Analysis 70, 102028, 2021
152021
X-ray scatter estimation using deep splines
P Roser, A Birkhold, A Preuhs, C Syben, L Felsner, E Hoppe, N Strobel, ...
IEEE Transactions on Medical Imaging 40 (9), 2272-2283, 2021
132021
Known operator learning enables constrained projection geometry conversion: Parallel to cone-beam for hybrid MR/X-ray imaging
C Syben, B Stimpel, P Roser, A Dörfler, A Maier
IEEE Transactions on Medical Imaging 39 (11), 3488-3498, 2020
132020
Machine Learning for Medical Image Reconstruction
B Bier, K Aschoff, C Syben, M Unberath, M Levenston, G Gold, R Fahrig, ...
Springer, 2018
132018
Automatic Thrombus Detection in Non-enhanced Computed Tomography Images in Patients With Acute Ischemic Stroke.
P Löber, B Stimpel, C Syben, AK Maier, H Ditt, P Schramm, B Raczkowski, ...
VCBM, 125-129, 2017
132017
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Artiklar 1–20