Gibbs-ringing artifact in magnitude images obtained by using partial Fourier (PF) acquisition and zero filling interpolation is modeled analytically, and a correction pipeline based on modifying the local subvoxel-shifts method is proposed. With the understanding of oscillating convolution kernel due to the PF acquisition, the ringings in magnitude images can be robustly removed without the need of ad hoc image models and tuning parameters. The effects of ringings on diffusion metrics are further demonstrated in numerical phantoms and in vivo diffusion data. The proposed pipeline removes most ringings in magnitude images and stabilizes estimations of diffusion metrics.
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