A robust, easy-to-deploy non-uniform Fast Fourier Transform in TensorFlow.
Project description
TF KB-NUFFT
GitHub |
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
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Fessler, J. A., & Sutton, B. P. (2003). Nonuniform fast Fourier transforms using min-max interpolation. IEEE transactions on signal processing, 51(2), 560-574.
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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.
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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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