Python Non-Uniform Fast Fourier Transform (PyNUFFT): multi-dimensional non-Cartesian image reconstruction package for heterogeneous platforms and applications to MRI. This paper reports the development of a Python Non-Uniform Fast Fourier Transform (PyNUFFT) package, which accelerates non-Cartesian image reconstruction on heterogeneous platforms. Scientific computing with Python encompasses a mature and integrated environment. The NUFFT algorithm has been extensively used for non-Cartesian image reconstruction but previously there was no native Python NUFFT library. The current PyNUFFT software enables multi-dimensional NUFFT on heterogeneous platforms. 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 were employed to accelerate PyNUFFT. The PyNUFFT package has been tested on multi-core CPU and GPU, with acceleration factors of 6.3 - 9.5× on a 32 thread CPU platform and 5.4 - 13× on the GPU.
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References in zbMATH (referenced in 4 articles )
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- Barnett, Alex H.: Aliasing error of the (\exp(\beta\sqrt1-z^2)) kernel in the nonuniform fast Fourier transform (2021)
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- Barnett, Alexander H.; Magland, Jeremy; af Klinteberg, Ludvig: A parallel nonuniform fast Fourier transform library based on an “exponential of semicircle” kernel (2019)
- Jyh-Miin Lin: Python Non-Uniform Fast Fourier Transform (PyNUFFT): multi-dimensional non-Cartesian image reconstruction package for heterogeneous platforms and applications to MRI (2017) arXiv