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Convolutional Analysis Operator Learning by End-to-End Training of Iterative Neural Networks., , , , and . ISBI, page 1-5. IEEE, (2022)Learning Regularization Parameter-Maps for Variational Image Reconstruction Using Deep Neural Networks and Algorithm Unrolling., , , , , , , , and . SIAM J. Imaging Sci., 16 (4): 2202-2246 (December 2023)Unsupervised Adaptive Neural Network Regularization for Accelerated Radial Cine MRI., , , , and . CoRR, (2020)Clinical quantitative cardiac imaging for the assessment of myocardial ischaemia, , , , , , , , , and 14 other author(s). Nat Rev Cardiol, 17 (7): 427--450 (July 2020)Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI with Limited Data., , , , and . CoRR, (2019)PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction., , , and . CoRR, (2023)An End-To-End-Trainable Iterative Network Architecture for Accelerated Radial Multi-Coil 2D Cine MR Image Reconstruction., , , and . CoRR, (2021)Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI With Limited Training Data., , , , and . IEEE Trans. Medical Imaging, 39 (3): 703-717 (2020)Quantitative MR Image Reconstruction Using Parameter-Specific Dictionary Learning With Adaptive Dictionary-Size and Sparsity-Level Choice., , , , and . IEEE Trans. Biomed. Eng., 71 (2): 388-399 (February 2024)NoSENSE: Learned Unrolled Cardiac MRI Reconstruction Without Explicit Sensitivity Maps., and . STACOM@MICCAI, volume 14507 of Lecture Notes in Computer Science, page 454-466. Springer, (2023)