Integrated Image Reconstruction and Gradient Nonlinearity Correction

The gradient fields used for spatial encoding in clinical MRI are never truly linear over the imaging FOV. As standard MRI signal models presume gradient linearity, reconstructed images exhibit geometric distortion unless gradient deviations are properly accounted for. Geometric distortion is typically corrected via image-domain interpolation. Although this approach is straightforward, it does not account for the effects of finite sampling, undersampling, or noise, and may degrade spatial resolution. In this work, we propose a correction strategy that accounts for gradient nonlinearity during rather than after k-space to image reconstruction, and lessens the tradeoff between geometric accuracy and spatial resolution.

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