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20172022
most citedSpatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI with Limited Data

87 citations · 253 across the 8 of their papers we have counts for

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eess.IV2022

Convolutional Dictionary Learning by End-To-End Training of Iterative Neural Networks

Andreas Kofler, Christian Wald, Tobias Schaeffter +2

Sparsity-based methods have a long history in the field of signal processing and have been successfully applied to various image reconstruction problems. The involved sparsifying t…

eess.IV2022

Convolutional Analysis Operator Learning by End-To-End Training of Iterative Neural Networks

Andreas Kofler, Christian Wald, Tobias Schaeffter +2

The concept of sparsity has been extensively applied for regularization in image reconstruction. Typically, sparsifying transforms are either pre-trained on ground-truth images or…