Abstract #3639
Fast Non-Cartesian Reconstruction with Pruned Fast Fourier Transform
Frank Ong 1 , Martin Uecker 1 , Wenwen Jiang 2 , and Michael Lustig 1
1
Electrical Engineering and Computer
Sciences, University of California, Berkeley, Berkeley,
California, United States,
2
Bioengineering,
UC Berkeley/UCSF, Berkeley, California, United States
We present a method to accelerate almost all
non-Cartesian MR reconstruction methods using pruned
FFT. Contrary to common belief, we show that no memory
overhead is required for any oversampling factors in
non-Cartesian reconstruction. For iterative methods, we
also propose partial pruning to approximate the
non-Cartesian Fourier Transform operator to speed up
each iteration while guaranteeing convergence. We apply
our proposed method on compressed sensing and parallel
imaging reconstruction of in vivo datasets and show that
our proposed method reduces the computation time for
non-Cartesian image reconstruction with gridding and
toeplitz-circulant embedding.
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