Kerstin Hammernik
TitleCited byYear
Learning a variational network for reconstruction of accelerated MRI data
K Hammernik, T Klatzer, E Kobler, MP Recht, DK Sodickson, T Pock, ...
Magnetic resonance in medicine 79 (6), 3055-3071, 2018
1902018
A multi-center milestone study of clinical vertebral CT segmentation
J Yao, JE Burns, D Forsberg, A Seitel, A Rasoulian, P Abolmaesumi, ...
Computerized Medical Imaging and Graphics 49, 16-28, 2016
432016
Variational Networks: Connecting Variational Methods and Deep Learning
E Kobler, T Klatzer, K Hammernik, T Pock
German Conference on Pattern Recognition, 281-293, 2017
352017
Learning Joint Demosaicing and Denoising Based on Sequential Energy Minimization
T Klatzer, K Hammernik, P Knobelreiter, T Pock
Computational Photography (ICCP), 2016 IEEE International Conference on, 1-11, 2016
302016
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
262017
Assessment of the generalization of learned image reconstruction and the potential for transfer learning
F Knoll, K Hammernik, E Kobler, T Pock, MP Recht, DK Sodickson
Magnetic resonance in medicine 81 (1), 116-128, 2019
232019
Spray Drying of Aqueous Salbutamol Sulfate Solutions Using the Nano Spray Dryer B-90—The Impact of Process Parameters on Particle Size
EM Littringer, S Zellnitz, K Hammernik, V Adamer, H Friedl, NA Urbanetz
Drying Technology 31 (12), 1346-1353, 2013
222013
Learning a Variational Model for Compressed Sensing MRI Reconstruction
K Hammernik, F Knoll, D Sodickson, T Pock
Proceedings of the International Society of Magnetic Resonance in Medicine …, 2016
212016
Vertebrae Segmentation in 3D CT Images Based on a Variational Framework
K Hammernik, T Ebner, D Stern, M Urschler, T Pock
Recent Advances in Computational Methods and Clinical Applications for Spine …, 2015
182015
L2 or not L2: impact of loss function design for deep learning MRI reconstruction
K Hammernik, F Knoll, DK Sodickson, T Pock
ISMRM 25th Annual Meeting, 0687, 2017
52017
Automatic Intervertebral Disc Localization and Segmentation in 3D MR Images Based on Regression Forests and Active Contours
M Urschler, K Hammernik, T Ebner, D Štern
International Workshop on Computational Methods and Clinical Applications …, 2015
52015
Variational Adversarial Networks for Accelerated MR Image Reconstruction
K Hammernik, E Kobler, T Pock, MP Recht, DK Sodickson, F Knoll
Joint Annual Meeting ISMRM-ESMRMB 2018, 2018
32018
Variational photoacoustic image reconstruction with spatially resolved projection data
K Hammernik, T Pock, R Nuster
Photons Plus Ultrasound: Imaging and Sensing 2017 10064, 100643I, 2017
32017
On the influence of sampling pattern design on deep learning-based MRI reconstruction
K Hammernik, F Knoll, DK Sodickson, T Pock
ISMRM 25th Annual Meeting, 0644, 2017
22017
Accelerated knee imaging using a deep learning based reconstruction
F Knoll, K Hammernik, E Garwood, A Hirschmann, L Rybak, M Bruno, ...
ISMRM 25th Annual Meeting, 0645, 2017
22017
Variational Deep Learning for Low-Dose Computed Tomography
E Kobler, M Muckley, B Chen, F Knoll, K Hammernik, T Pock, D Sodickson, ...
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
12018
Trainable Regularization for Multi-frame Superresolution
T Klatzer, D Soukup, E Kobler, K Hammernik, T Pock
German Conference on Pattern Recognition, 90-100, 2017
12017
Convex framework for 2D & 3D image segmentation using shape constraints
K Hammernik
12015
Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction
F Knoll, K Hammernik, C Zhang, S Moeller, T Pock, DK Sodickson, ...
arXiv preprint arXiv:1904.01112, 2019
2019
Sparse-View CT Reconstruction Using Wasserstein GANs
F Thaler, K Hammernik, C Payer, M Urschler, D Štern
International Workshop on Machine Learning for Medical Image Reconstruction …, 2018
2018
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Articles 1–20