Erich Kobler
Erich Kobler
Institute of Computer Graphics and Vision, Graz Universtiy of Technology
Bestätigte E-Mail-Adresse bei
Zitiert von
Zitiert von
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
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
Variational networks: connecting variational methods and deep learning
E Kobler, T Klatzer, K Hammernik, T Pock
German conference on pattern recognition, 281-293, 2017
Variational Networks: An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration
A Effland, E Kobler, K Kunisch, T Pock
Journal of Mathematical Imaging and Vision, 1-21, 2020
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
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
Total deep variation: A stable regularizer for inverse problems
E Kobler, A Effland, K Kunisch, T Pock
arXiv preprint arXiv:2006.08789, 2020
SparseCT: System concept and design of multislit collimators
B Chen, E Kobler, MJ Muckley, AD Sodickson, T O'Donnell, T Flohr, ...
Medical physics 46 (6), 2589-2599, 2019
Total Deep Variation for Linear Inverse Problems
E Kobler, A Effland, K Kunisch, T Pock
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions
PM Johnson, MJ Muckley, M Bruno, E Kobler, K Hammernik, T Pock, ...
International Workshop on Machine Learning for Medical Image Reconstruction …, 2019
Trainable regularization for multi-frame superresolution
T Klatzer, D Soukup, E Kobler, K Hammernik, T Pock
German Conference on Pattern Recognition, 90-100, 2017
Time discrete geodesics in deep feature spaces for image morphing
A Effland, E Kobler, T Pock, M Rumpf
International Conference on Scale Space and Variational Methods in Computer …, 2019
Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data
A Effland, E Kobler, A Brandenburg, T Klatzer, L Neuhäuser, M Hölzel, ...
International journal of computer assisted radiology and surgery 14 (4), 587-599, 2019
Image Morphing in Deep Feature Spaces: Theory and Applications
A Effland, E Kobler, T Pock, M Rajković, M Rumpf
Journal of Mathematical Imaging and Vision, 1-19, 2020
Analysis of the influence of deviations between training and test data in learned image reconstruction
F Knoll, K Hammernik, E Kobler, T Pock, DK Sodickson, MP Recht
ISMRM Workshop on Machine Learning, 2018
Variational Networks for Joint Image Reconstruction and Classification of Tumor Immune Cell Interactions in Melanoma Tissue Sections
A Effland, M Hölzel, T Klatzer, E Kobler, J Landsberg, L Neuhäuser, ...
Bildverarbeitung für die Medizin 2018, 334-340, 2018
Shared Prior Learning of Energy-Based Models for Image Reconstruction
T Pinetz, E Kobler, T Pock, A Effland
arXiv preprint arXiv:2011.06539, 2020
Accelerating Prostate Diffusion-weighted MRI Using a Guided Denoising Convolutional Neural Network: Retrospective Feasibility Study
EA Kaye, EA Aherne, C Duzgol, I Häggström, E Kobler, Y Mazaheri, ...
Radiology: Artificial Intelligence 2 (5), e200007, 2020
Effect of Multislit Collimator Motion On SparseCT Image Quality for Low-Dose CT Examinations
B Chen, E Kobler, T Allmendinger, A Sodickson, D Sodickson, R Otazo
Medical Physics, E504-E505, 2019
Learning variational models for blind image deconvolution
E Kobler
Graz University of Technology, 2014
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