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Abstract #3506

Parameter Optimization of Wave-CAIPI Based on Theoretical Analysis

Zhilang Qiu1, Haifeng Wang1, Leslie Ying2, Xin Liu1, and Dong Liang1

1Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 2Department of Biomedical Engineering and Department of Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, United States

Wave-CAIPI is an novel 3D imaging technique with corkscrew trajectory in k-space to reduce g-factor penalty and speed up MRI acquisitions. The sinusoidal gradient parameters of Wave-CAIPI, amplitude and cycles, play an important role since they determine the point spread function of the trajectory and thus the final reconstruction. However, how to choose the optimal sinusoidal gradient parameters which leads to the minimal g-factor has not been exploited. In this work, we theoretically analyzed the influence of the sinusoidal gradient parameters on g-factor. An optimization algorithm which can be automatically conducted is then proposed to optimize these parameters for achieving minimal g-factor penalty. The simulations show that using the optimized sinusoidal gradient parameters can achieve lower g-factor penalty in Wave-CAIPI reconstructions.

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