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

Journal of Imaging

Jyh-Miin Lin¹ 

[1] Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK;

关键词: heterogeneous system architecture (HSA);    graphic processing unit (GPU);    multi-core system;    magnetic resonance imaging (MRI);    total variation (TV);   

DOI  :  10.3390/jimaging4030051

来源: DOAJ

【 摘 要 】

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 6.3–9.5× on a 32-thread CPU platform and 5.4–13× on a GPU.

【 授权许可】

Unknown