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Abstract #3719

Non-Cartesian MR Image Reconstruction with Integrated Gradient Nonlinearity and Off Resonance Correction

Shengzhen Tao 1 , Joshua D Trzasko 1 , Yunhong Shu 1 , John Huston III 1 , Paul T Weavers 1 , and Matt A Bernstein 1

1 Radiology, Mayo Clinic, Rochester, MN, United States

Due to engineering limitations, achieving perfect gradient linearity across the imaging field-of-view is infeasible. Gradient nonlinearity(GNL), if not accounted for, causes image geometrical distortion, which is conventionally corrected by image-domain interpolation. Direct interpolation techniques, however, exert smoothing effects on corrected images which results in resolution loss. In non-Cartesian MRI, B0 inhomogeneity can also cause image blurring. In this work, a non-iterative gridding reconstruction framework with integrated GNL and B0 off-resonance correction is developed for non-Cartesian MRI. The proposed strategy can mitigate the image blurring that occurs in standard interpolation-based GNL-correction and from B0 inhomogeneity while still effectively correcting geometrical distortion.

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