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Abstract #4559

Dynamic MRI Reconstruction Combining Tensor Nuclear Norm and Casorati Matrix Nuclear Norm

Yinghao Zhang1, Yue Hu1, and Xin Lu2
1School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China, 2School of Computer Science and Informatics, De Montfort University, Leicester, United Kingdom


Low-rank tensor models have been applied in accelerating dynamic magnetic resonance imaging (dMRI). Recently, a new tensor nuclear norm based on t-SVD has been proposed and applied to tensor completion. Inspired by the different properties of the tensor nuclear norm (TNN) and the Casorati matrix nuclear norm (MNN), we introduce a novel dMRI reconstruction method combining TNN and Casorati MNN, which we term as TMNN. Moreover, we convert the the TMNN dMRI reconstruction problem into a simple tensor completion problem, which can be efficiently solved by the alternating direction method of multipliers (ADMM).

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