Abstract #4365
Randomized Golden Ratio Sampling For Highly Accelerated Dynamic Imaging
Yinghua Zhu 1 , Yi Guo 1 , R. Marc Lebel 2 , Meng Law 3 , and Krishna Nayak 1
1
Electrical Engineering Department,
University of Southern California, Los Angeles, CA,
United States,
2
GE
Healthcare, Calgary, Alberta, Canada,
3
Radiology
Department, University of Southern California, Los
Angeles, CA, United States
Compressed sensing has shown great potential in
accelerating dynamic contrast enhanced MRI. Conventional
Poisson-disc (PD) and Cartesian golden ratio (GR) radial
schemes on the ky-kz plane of the 3D k-space are
inefficient due to computation time and sub-optimal
sparsity, respectively. We propose a novel randomized GR
(RGR) sampling that is fast in sampling pattern
generation on an MRI scanner, and flexible in temporal
resolution selection in the reconstruction. We show and
compare the results from PD, GR and RGR in retrospective
studies using clinical DCE data. The proposed method
yields promising results for highly accelerated DCE-MRI.
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