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Abstract #2887

Speedup of iterative k-t SENSE reconstruction using the multidimensional fast Fourier transform for arbitrary periodic grids

Adam Johansson1, James M Balter1, and Yue Cao1,2,3

1Radiation Oncology, University of Michigan, Ann Arbor, MI, United States, 2Radiology, University of Michigan, Ann Arbor, MI, United States, 3Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States

The multidimensional fast Fourier transform (MFFT) for arbitrary n-dimensional periodic grids allows images with non-cuboid voxels and fields of view (FOV) to be reconstructed efficiently. In this study, we apply the MFFT with a modified Smith normal form to iterative k-t SENSE reconstruction of data from a golden-angle stack-of-stars DCE-MRI sequence to produce a 4-D image with a non-cuboid FOV tailored to fit tight around the imaged subject. Compared to FFT-based reconstruction on a tight-fitting cuboid FOV, the non-cuboid MFFT reduced reconstruction time by 18% and memory usage by 11% while producing voxel values identical to those found in the reconstruction domain of the cuboid FOV.

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