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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…
eess.IV2020
Neural Networks-based Regularization for Large-Scale Medical Image Reconstruction
Andreas Kofler, Markus Haltmeier, Tobias Schaeffter +4
In this paper we present a generalized Deep Learning-based approach for solving ill-posed large-scale inverse problems occuring in medical image reconstruction. Recently, Deep Lear…
eess.IV2019
Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI with Limited Data
Andreas Kofler, Marc Dewey, Tobias Schaeffter +2
In this work we reduce undersampling artefacts in two-dimensional () golden-angle radial cine cardiac MRI by applying a modified version of the U-net. We train the network on $…