Abstract #0610
A Clinically Applicable Scheme of MRI Trajectory Optimization for 3D Cartesian Acquisition
Enhao Gong 1 , Feng Huang 2 , and John M Pauly 1
1
Electrical Engineering, Stanford University,
Stanford, CA, United States,
2
Philips
Healthcare, Gainesville, FL, United States
Random undersampling is an important component used with
Parallel Imaging (PI) and Compressed Sensing (CS) and
their combination (PI-CS) for fast acquisition.
Optimized pseudo-random trajectory results in better
reconstruction yet the optimization is computational
costly. Lately, we proposed an efficient scheme for 1D
random undersampling optimization using stochastic
method and reference k-space. Here we extended and
improved the scheme to optimize the 2D Cartesian
undersampling for both PI and CS using Nonlinear Grappa
Operator and Coherence based objective function. In-vivo
experiments demonstrated greater performance improvement
for reconstruction using PI-CS. The scheme is also
applicable for non-Cartesian undersampling.
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