CODEC: Covariance-driven Parallel Imaging for NonCartesian Sampling Trajectories

This work presents a new parallel imaging method. It is a k-space convolution method that is quite independent of the sampling geometry, and does not require training, and therefore is quite suitable for nonCartesian sampling. The method is described, and 2D and 3D examples are shown.

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