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Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery., , , , , and . CoRR, (2018)A New Deep Learning Network for Mitigating Limited-view and Under-sampling Artifacts in Ring-shaped Photoacoustic Tomography., , , , , , and . Comput. Medical Imaging Graph., (2020)Learning Data Consistency and its Application to Dynamic MR Imaging., , , , , , , and . IEEE Trans. Medical Imaging, 40 (11): 3140-3153 (2021)Computational MRI: Compressive Sensing and Beyond From the Guest Editors., , , and . IEEE Signal Process. Mag., 37 (1): 21-23 (2020)M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging., , , and . ISBI, page 19-22. IEEE, (2017)Sparsity-based PET image reconstruction using MRI learned dictionaries., , , and . ISBI, page 1087-1090. IEEE, (2014)Image reconstruction from phased-array MRI data based on multichannel blind deconvolution., , , , and . ISBI, page 760-763. IEEE, (2010)Noise behavior of MR brain reconstructions using compressed sensing., , , and . EMBC, page 5155-5158. IEEE, (2013)A hybrid total-variation minimization approach to compressed sensing., , , and . ISBI, page 74-77. IEEE, (2012)Accelerating dynamic magnetic resonance imaging by nonlinear sparse coding., , , , and . ISBI, page 510-513. IEEE, (2016)