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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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