A U-Nets Cascade for Sparse View Computed Tomography. - Andreas Kofler; Markus Haltmeier; Christoph Kolbitsch; Marc Kachelrieß; Marc Dewey (MLMIR@MICCAI, 2018)

Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI with Limited Data. - Andreas Kofler; Marc Dewey; Tobias Schaeffter; Christian Wald; Christoph Kolbitsch (CoRR, 2019)

Neural Networks-based Regularization of Large-Scale Inverse Problems in Medical Imaging. - Andreas Kofler; Markus Haltmeier; Tobias Schaeffter; Marc Kachelrieß; Marc Dewey; Christian Wald; Christoph Kolbitsch (CoRR, 2019)

Unsupervised Adaptive Neural Network Regularization for Accelerated Radial Cine MRI. - Andreas Kofler; Marc Dewey; Tobias Schaeffter; Christoph Kolbitsch; Markus Haltmeier (CoRR, 2020)

Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI With Limited Training Data. - Andreas Kofler; Marc Dewey; Tobias Schaeffter; Christian Wald; Christoph Kolbitsch (IEEE Trans. Medical Imaging, 2020)

An End-To-End-Trainable Iterative Network Architecture for Accelerated Radial Multi-Coil 2D Cine MR Image Reconstruction. - Andreas Kofler; Markus Haltmeier; Tobias Schaeffter; Christoph Kolbitsch (CoRR, 2021)

Convolutional Dictionary Learning by End-To-End Training of Iterative Neural Networks. - Andreas Kofler; Christian Wald; Tobias Schaeffter; Markus Haltmeier; Christoph Kolbitsch (EUSIPCO, 2022)

Convolutional Analysis Operator Learning by End-to-End Training of Iterative Neural Networks. - Andreas Kofler; Christian Wald; Tobias Schaeffter; Markus Haltmeier; Christoph Kolbitsch (ISBI, 2022)

NoSENSE: Learned Unrolled Cardiac MRI Reconstruction Without Explicit Sensitivity Maps. - Felix Frederik Zimmermann; Andreas Kofler (STACOM@MICCAI, 2023)

Learning Regularization Parameter-Maps for Variational Image Reconstruction Using Deep Neural Networks and Algorithm Unrolling. - Andreas Kofler; Fabian Altekrüger; Fatima Antarou Ba; Christoph Kolbitsch; Evangelos Papoutsellis; David Schote; Clemens Sirotenko; Felix Frederik Zimmermann; Kostas Papafitsoros (SIAM J. Imaging Sci., 2023)

PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction. - Felix F. Zimmermann; Christoph Kolbitsch; Patrick Schuenke; Andreas Kofler (IEEE Trans. Computational Imaging, 2024)

Quantitative MR Image Reconstruction Using Parameter-Specific Dictionary Learning With Adaptive Dictionary-Size and Sparsity-Level Choice. - Andreas Kofler; Kirsten Miriam Kerkering; Laura Göschel; Ariane Fillmer; Christoph Kolbitsch (IEEE Trans. Biomed. Eng., 2024)

Joint $ text{B}_{0}$ and Image Reconstruction in Low-Field MRI by Physics-Informed Deep-Learning. - David Schote; Lukas Winter; Christoph Kolbitsch; Georg Rose; Oliver Speck; Andreas Kofler (IEEE Trans. Biomed. Eng., 2024)

Deep Unrolling for Learning Optimal Spatially Varying Regularisation Parameters for Total Generalised Variation. - Thanh Trung Vu; Andreas Kofler; Kostas Papafitsoros (SSVM (1), 2025)

MR imaging in the low-field: Leveraging the power of machine learning. - Andreas Kofler; Dongyue Si; David Schote; René M. Botnar; Christoph Kolbitsch; Claudia Prieto (CoRR, 2025)

Learning Spatially Adaptive ℓ1-Norms Weights for Convolutional Synthesis Regularization. - Andreas Kofler; Luca Calatroni; Christoph Kolbitsch; Kostas Papafitsoros (CoRR, 2025)

Robust Myocardial Perfusion MRI Quantification With DeepFermi. - Sherine Brahma; Andreas Kofler; Felix F. Zimmermann; Tobias Schaeffter; Amedeo Chiribiri; Christoph Kolbitsch (IEEE Trans. Biomed. Eng., 2025)

MRpro - open PyTorch-based MR reconstruction and processing package. - Felix Frederik Zimmermann; Patrick Schuenke; Christoph S. Aigner; Bill A. Bernhardt; Mara Guastini; Johannes Hammacher; Noah Jaitner; Andreas Kofler; Leonid Lunin; Stefan Martin; Catarina Redshaw Kranich; Jakob Schattenfroh; et al. (CoRR, 2025)