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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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