Campbell-Washburn, AE;
Atkinson, D;
Nagy, Z;
Chan, RW;
Josephs, O;
Lythgoe, MF;
Ordidge, RJ;
(2016)
Using the robust principal component analysis algorithm to remove RF spike artifacts from MR images.
Magnetic Resonance in Medicine
, 75
(6)
pp. 2517-2525.
10.1002/mrm.25851.
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Abstract
Brief bursts of RF noise during MR data acquisition ("k-space spikes") cause disruptive image artifacts, manifesting as stripes overlaid on the image. RF noise is often related to hardware problems, including vibrations during gradient-heavy sequences, such as diffusion-weighted imaging. In this study, we present an application of the Robust Principal Component Analysis (RPCA) algorithm to remove spike noise from k-space.
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