Abstract #2410

kz-GRAPPA for 3D parallel imaging with localized estimation of interpolation kernels

Steen Moeller¹, Sudhir Ramanna¹, Essa Yacoub¹, Kamil Ugurbil¹, and Mehmet Akcakaya^1,2

¹University of Minnesota, Minneapolis, MN, United States, ²Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States

A k_z-dependent shift-variant 3D GRAPPA approach for reconstructing 2D under-sampled k-space is proposed. The method results in equal or lower g-factors compared to a conventional shift-invariant 3D kernel. In turn, this permits higher 2D k_y-k_z accelerations, and promises significant advantages for functional and diffusion imaging. The method is demonstrated with anatomical and diffusion imaging using thin slabs.

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