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Abstract #5166

Nonlinear SPIRiT using a second order virtual coil for improved parallel imaging reconstruction

Sen Jia1, Yanjie Zhu1, Lei Zhang1, Yiu-cho Chung1, Jing Cheng1, Leslie Ying2, Xin Liu1, Hairong Zheng1, and Dong Liang1

1Shenzhen Institutes of Advanced Technology, Shenzhen, People's Republic of China, 2The state University of New York (SUNY) at Buffalo, United States

The nonlinear relationship between missing and acquired data in k-space has been proved in nonlinear GRAPPA. In this work, we propose nonlinear SPIRiT which integrates the polynomial kernel method into SPIRiT via a simple second-order virtual coil approach. The proposed method represents the relationship between missing and acquired data in k-space of SPIRiT using a more accurate nonlinear model. In vivo results demonstrated that nonlinear SPIRiT could suppress aliasing artifact or noise better than SPIRiT, and was applicable to more acceleration scenarios than nonlinear GRAPPA.

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