Abstract #1045

A scalable composite through-time radial GRAPPA method

Seng-Wei Chieh¹, Steen Moeller², Mehmet Akcakaya¹, and Mostafa Kaveh¹

¹Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States, ²Center for Magnetic Resonance Research, University of Minnesota

Through-time radial GRAPPA showed promising reconstruction for cardiac imaging. However, it's challenging to extend 3D Kooshball trajectory because of long calibration scans. We propose a novel and flexible data-driven calibration method. The MRXCAT numerical phantom image results show image similarity with through-time radial GRAPPA.

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