Abstract #2535
Evaluation of GLACIER sampling for 3D DCE-MRI
Yinghua Zhu 1 , Yi Guo 1 , Sajan Goud Lingala 1 , R. Marc Lebel 2 , Meng Law 1 , and Krishna Nayak 1
1
University of Southern California, Los
Angeles, CA, United States,
2
GE
Healthcare, Calgary, Canada
The proposed GoLden Angle CartesIan Encoded
Randomization (GLACIER) sampling scheme combines two
existing techniques, Poisson ellipsoid pseudorandom
undersampling and golden angle (GA) Cartesian sampling.
GLACIER randomizes ky-kz phase encode along golden angle
radials with designed sampling probability. Constrained
reconstruction results of GLACIER are compared with two
conventional methods in retrospective studies.
Normalized root-mean-square error is used as an
objective image quality metric. GLACIER algorithm is
fast and allows online sampling pattern generation.
GLACIER shows comparable results with Poisson ellipsoid
and improved quality over conventional GA method in
retrospective studies.
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