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 | 273 | 2018 |
Deep learning computed tomography T Würfl, FC Ghesu, V Christlein, A Maier Medical Image Computing and Computer-Assisted Intervention-MICCAI 2016: 19th …, 2016 | 217 | 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 | 194 | 2019 |
Adversarial and perceptual refinement for compressed sensing MRI reconstruction M Seitzer, G Yang, J Schlemper, O Oktay, T Würfl, V Christlein, T Wong, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 135 | 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, A Maier German Medical Data Sciences: Visions and Bridges, 202-206, 2017 | 129 | 2017 |
Some investigations on robustness of deep learning in limited angle tomography Y Huang, T Würfl, K Breininger, L Liu, G Lauritsch, A Maier Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 118 | 2018 |
A deep learning architecture for limited-angle computed tomography reconstruction K Hammernik, T Würfl, T Pock, A Maier Bildverarbeitung für die Medizin 2017: Algorithmen-Systeme-Anwendungen …, 2017 | 108* | 2017 |
Torchmeta: A meta-learning library for pytorch T Deleu, T Würfl, M Samiei, JP Cohen, Y Bengio arXiv preprint arXiv:1909.06576, 2019 | 103 | 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 | 66 | 2018 |
Frangi-net W Fu, K Breininger, R Schaffert, N Ravikumar, T Würfl, J Fujimoto, E Moult, ... Bildverarbeitung für die Medizin 2018: Algorithmen-Systeme-Anwendungen …, 2018 | 45 | 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 | 29 | 2017 |
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 | 28 | 2017 |
International Conference on Medical Image Computing and Computer Assisted Intervention M Seitzer, G Yang, J Schlemper, O Oktay, T Würfl, V Christlein, T Wong, ... Springer,, 2018 | 27 | 2018 |
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 | 25 | 2019 |
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 | 25 | 2018 |
Deep‐learning‐based pipeline for module power prediction from electroluminescense measurements M Hoffmann, C Buerhop‐Lutz, L Reeb, T Pickel, T Winkler, B Doll, T Würfl, ... Progress in Photovoltaics: Research and Applications 29 (8), 920-935, 2021 | 21 | 2021 |
U-Net for SPECT Image Denoising MP Reymann, T Würfl, P Ritt, B Stimpel, M Cachovan, AH Vija, A Maier 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC …, 2019 | 21 | 2019 |
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 | 19 | 2018 |
Calibration‐free beam hardening reduction in x‐ray CBCT using the epipolar consistency condition and physical constraints T Würfl, M Hoffmann, A Aichert, AK Maier, N Maaß, F Dennerlein Medical physics 46 (12), e810-e822, 2019 | 18 | 2019 |
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 | 18 | 2017 |