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K-space refinement in deep learning MR reconstruction via regularizing scan specific SPIRiT-based self consistency.

, , , , and . ICCVW, page 3991-4000. IEEE, (2021)

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K-space refinement in deep learning MR reconstruction via regularizing scan specific SPIRiT-based self consistency., , , , and . ICCVW, page 3991-4000. IEEE, (2021)GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction., , , , , , , , and . CoRR, (2022)VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction., , , , , , , , and . MIDL, volume 172 of Proceedings of Machine Learning Research, page 325-352. PMLR, (2022)Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges., , , , , , , , and . CoRR, (2019)Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction., , , , , , and . MICCAI (6), volume 13436 of Lecture Notes in Computer Science, page 737-747. Springer, (2022)Neural Proximal Gradient Descent for Compressive Imaging., , , , , , and . NeurIPS, page 9596-9606. (2018)Learned Compression of High Dimensional Image Datasets., , , and . CVPR Workshops, page 1747-1751. IEEE, (2022)Evaluation of Patient Positioning to Mitigate RF-induced Heating of Cardiac Implantable Electronic Devices for Pediatric MRI Exams., , , , and . EMBC, page 5027-5030. IEEE, (2021)Practical parallel imaging compressed sensing MRI: Summary of two years of experience in accelerating body MRI of pediatric patients., , , , , , and . ISBI, page 1039-1043. IEEE, (2011)Fast Unsupervised MRI Reconstruction Without Fully-Sampled Ground Truth Data Using Generative Adversarial Networks., , , and . ICCVW, page 3971-3980. IEEE, (2021)