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MR Fingerprinting Reconstruction based on Structured Low-rank Approximation and Subspace Modeling
Peng Li1 and Yue Hu1
1Harbin Institute of Technology, Harbin, China
MR Fingerprinting Reconstruction based on Structured Low-rank Approximation and Subspace Modeling.
Fig.2 Reconstructed maps of T1, T2 and PD, using the 5% sampled noiseless data. The acquisition length is $$$L=400$$$.
Fig.1 Illustration of the structure of the lifted matrix $$${\cal T}(\mathbf{x})$$$: The rows of the matrix are 3-D neighborhoods of the gradient-weighted $$$k$$$-space samples.