David S. Smith1, Ryan Robison, 12, E Brian Welch1
1Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States; 2Philips Healthcare, Cleveland, OH, United States
We present a method using concepts from compressed sensing to automatically detect and eliminate radio frequency spike noise from MRI data sets. The spikes are located by their effect on the total variation of the image. The spikes are then deleted from the full data set, creating a very slightly undersampled data set, which is then reconstructed in a TV-regularized compressed sensing MRI reconstruction. Since the data is almost completely Nyquist sampled, this method introduces no artifacts and produces images with normalized mean square error two orders of magnitude smaller than both zeroing of the spiked data and Fourier interpolation.
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