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A robust, easy-to-deploy non-uniform Fast Fourier Transform in TensorFlow.

Project description

TF KB-NUFFT

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About

This package is a verly early-stage and modest adaptation to TensorFlow of the torchkbnufft package written by Matthew Muckley for PyTorch. Please cite his work appropriately if you use this package.

References

  1. Fessler, J. A., & Sutton, B. P. (2003). Nonuniform fast Fourier transforms using min-max interpolation. IEEE transactions on signal processing, 51(2), 560-574.

  2. Beatty, P. J., Nishimura, D. G., & Pauly, J. M. (2005). Rapid gridding reconstruction with a minimal oversampling ratio. IEEE transactions on medical imaging, 24(6), 799-808.

  3. Feichtinger, H. G., Gr, K., & Strohmer, T. (1995). Efficient numerical methods in non-uniform sampling theory. Numerische Mathematik, 69(4), 423-440.

Citation

If you want to cite the package, you can use any of the following:

@conference{muckley:20:tah,
  author = {M. J. Muckley and R. Stern and T. Murrell and F. Knoll},
  title = {{TorchKbNufft}: A High-Level, Hardware-Agnostic Non-Uniform Fast Fourier Transform},
  booktitle = {ISMRM Workshop on Data Sampling \& Image Reconstruction},
  year = 2020
}

@misc{Muckley2019,
  author = {Muckley, M.J. et al.},
  title = {Torch KB-NUFFT},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/mmuckley/torchkbnufft}}
}

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