Tobias Würfl
Tobias Würfl
Siemens Healthineers
Verified email at - Homepage
Cited by
Cited by
Deep learning computed tomography: Learning projection-domain weights from image domain in limited angle problems
T Würfl, M Hoffmann, V Christlein, K Breininger, Y Huang, M Unberath, ...
IEEE transactions on medical imaging 37 (6), 1454-1463, 2018
Deep learning computed tomography
T Würfl, FC Ghesu, V Christlein, A Maier
International conference on medical image computing and computer-assisted …, 2016
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
Adversarial and perceptual refinement for compressed sensing MRI reconstruction
M Seitzer, G Yang, J Schlemper, O Oktay, T Würfl, V Christlein, T Wong, ...
International conference on medical image computing and computer-assisted …, 2018
Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series.
E Hoppe, G Körzdörfer, T Würfl, J Wetzl, F Lugauer, J Pfeuffer, AK Maier
GMDS 243, 202-206, 2017
A deep learning architecture for limited-angle computed tomography reconstruction
K Hammernik, T Würfl, T Pock, A Maier
Bildverarbeitung für die Medizin 2017, 92-97, 2017
Some investigations on robustness of deep learning in limited angle tomography
Y Huang, T Würfl, K Breininger, L Liu, G Lauritsch, A Maier
International Conference on Medical Image Computing and Computer-Assisted …, 2018
Torchmeta: A meta-learning library for pytorch
T Deleu, T Würfl, M Samiei, JP Cohen, Y Bengio
arXiv preprint arXiv:1909.06576, 2019
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
W Fu, K Breininger, R Schaffert, N Ravikumar, T Würfl, J Fujimoto, E Moult, ...
Bildverarbeitung für die Medizin 2018, 341-346, 2018
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
Empirical scatter correction using the epipolar consistency condition
M Hoffmann, T Würfl, N Maaß, F Dennerlein, A Aichert, AK Maier
5th International Conference on Image Formation in X-Ray Computed Tomography …, 2018
Epipolar Consistency Guided Beam Hardening Reduction-ECC 2
T Würfl, N Maaß, F Dennerlein, X Huang, AK Maier
14th International Meeting on Fully Three-Dimensional Image Reconstruction …, 2017
Deriving neural network architectures using precision learning: Parallel-to-fan beam conversion
C Syben, B Stimpel, J Lommen, T Würfl, A Dörfler, A Maier
German Conference on Pattern Recognition, 503-517, 2018
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
Deep learning for magnetic resonance fingerprinting: Accelerating the reconstruction of quantitative relaxation maps
E Hoppe, G Körzdörfer, M Nittka, T Würfl, J Wetzl, F Lugauer, M Schneider
Proceedings of the 26th Annual Meeting of ISMRM, Paris, France, 2018
Multiple device segmentation for fluoroscopic imaging using multi-task learning
K Breininger, T Würfl, T Kurzendorfer, S Albarqouni, M Pfister, ...
Intravascular imaging and computer assisted stenting and large-scale …, 2018
projection-to-projection translation for Hybrid X-ray and Magnetic Resonance imaging
B Stimpel, C Syben, T Würfl, K Breininger, P Hoelter, A Dörfler, A Maier
Scientific Reports 9 (1), 1-10, 2019
Transferability of deep learning algorithms for malignancy detection in confocal laser endomicroscopy images from different anatomical locations of the upper gastrointestinal tract
M Aubreville, M Goncalves, C Knipfer, N Oetter, T Würfl, H Neumann, ...
International Joint Conference on Biomedical Engineering Systems and …, 2018
Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images--A Cross-Site Robustness Assessment
M Aubreville, M Goncalves, C Knipfer, N Oetter, T Würfl, H Neumann, ...
arXiv preprint arXiv:1707.08149, 2017
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