English

Python Non-Uniform Fast Fourier Transform (PyNUFFT): multi-dimensional non-Cartesian image reconstruction package for heterogeneous platforms and applications to MRI

Medical Physics 2017-10-10 v1 Distributed, Parallel, and Cluster Computing Image and Video Processing

Abstract

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, \ell1 total-variation regularized ordinary least square (L1TV-OLS) and \ell1 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×\times on a 32 thread CPU platform and 5.4 - 13×\times on the GPU.

Keywords

Cite

@article{arxiv.1710.03197,
  title  = {Python Non-Uniform Fast Fourier Transform (PyNUFFT): multi-dimensional non-Cartesian image reconstruction package for heterogeneous platforms and applications to MRI},
  author = {Jyh-Miin Lin},
  journal= {arXiv preprint arXiv:1710.03197},
  year   = {2017}
}
R2 v1 2026-06-22T22:07:50.542Z