Di Cui1, Edward S. Hui2, and Peng Cao1
1Diagnostic Radiology, The University of Hong Kong, Hong Kong, China, 2Rehabilitation Science, The Hong Kong Polytechnic University, Hong Kong, China
1Diagnostic Radiology, The University of Hong Kong, Hong Kong, China, 2Rehabilitation Science, The Hong Kong Polytechnic University, Hong Kong, China
A k-space compression
strategy is proposed in a 3D alternating direction method of multipliers (ADMM)
framework in this study, with data and image series compressed, and
intermediate computation simplified.
(top) We
utilize a singular value decomposition (SVD) based k-space compression method. Image
series $$$x$$$ can be compressed with SVD. (bottom) in the iterative
reconstruction, the undersampling mask $$$P$$$ is replaced by $$$U_R^H P U_R $$$ with a size of R times R for a compressed
k-space, instead of computing vary large data matrices. Therefore, the iterative
reconstruction is performed on a compressed k-space.
3D
in vivo result, acquired using a stack of spiral MRF. Severe artifacts resisted
in the backprojection method, while they were effectively reduced with the
proposed method.