18108

Python Non-Uniform Fast Fourier Transform (PyNUFFT): An Accelerated Non-Cartesian MRI Package on a Heterogeneous Platform (CPU/GPU)

Jyh-Miin Lin
Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK
Journal of Imaging, 4(3), 51, 2018

@article{lin2018python,

   title={Python Non-Uniform Fast Fourier Transform (PyNUFFT): An Accelerated Non-Cartesian MRI Package on a Heterogeneous Platform (CPU/GPU)},

   author={Lin, Jyh-Miin},

   journal={Journal of Imaging},

   volume={4},

   number={3},

   pages={51},

   year={2018},

   publisher={Multidisciplinary Digital Publishing Institute}

}

A Python non-uniform fast Fourier transform (PyNUFFT) package has been developed to accelerate multidimensional non-Cartesian image reconstruction on heterogeneous platforms. Since scientific computing with Python encompasses a mature and integrated environment, the time efficiency of the NUFFT algorithm has been a major obstacle to real-time non-Cartesian image reconstruction with Python. The current PyNUFFT software enables multi-dimensional NUFFT accelerated on a heterogeneous platform, which yields an efficient solution to many non-Cartesian imaging problems. The PyNUFFT also provides several solvers, including the conjugate gradient method, l1 total variation regularized ordinary least square (L1TV-OLS), and l1 total variation regularized least absolute deviation (L1TV-LAD). Metaprogramming libraries have been employed to accelerate PyNUFFT. The PyNUFFT package has been tested on multi-core central processing units (CPUs) and graphic processing units (GPUs), with acceleration factors of 6.3-9.5x on a 32-thread CPU platform and 5.4-13x on a GPU.
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