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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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