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.
This abstract and the presentation materials are available to members only;
a login is required.
Join Here
