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Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues., , , , , , и . IEEE Signal Process. Mag., 37 (1): 128-140 (2020)Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction., , , , , , и . CoRR, (2019)On the Feasibility of Machine Learning Augmented Magnetic Resonance for Point-of-Care Identification of Disease., , , , , , , , , и . CoRR, (2023)Effect of an annular sleeve of high permittivity material on resonant modes and homogeneity of a birdcage coil., , , , , и . ISBI, стр. 1077-1080. IEEE, (2015)Combination of compressed sensing and parallel imaging for highly-accelerated dynamic MRI., , , , , и . ISBI, стр. 980-983. IEEE, (2012)An experimental system for detection and localization of hemorrhage using ultra-wideband microwaves with deep learning., , , , , , и . CoRR, (2023)Rapid free-breathing dynamic contrast-enhanced MRI using motion-resolved compressed sensing., , и . ISBI, стр. 889-892. IEEE, (2015)GrappaNet: Combining Parallel Imaging With Deep Learning for Multi-Coil MRI Reconstruction., , , , , и . CVPR, стр. 14303-14310. Computer Vision Foundation / IEEE, (2020)Differences between human and machine perception in medical diagnosis., , , , , , , , , и 11 other автор(ы). CoRR, (2020)The rapid imaging renaissance: sparser samples, denser dimensions, and glimmerings of a grand unified tomography., , , , , , , , и . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, том 9417 из SPIE Proceedings, стр. 94170G. SPIE, (2015)