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Abstract #1906

Improvement in Fat-Water Separation Using Modeled Gradient Impulse Response with Two-Point Dixon Radial Imaging

James Hao Wang1,2, Ali Pirasteh1,2, and Alan McMillan1,2
1Medical Physics, UW Madison, Madison, WI, United States, 2Radiology, UW Madison, Madison, WI, United States

Synopsis

Keywords: Image Reconstruction, Image Reconstruction, GIRF, Radial, PDFF, 2-Point Dixon

Motivation: Radial imaging is desirable for whole body imaging due to its motion robustness. However, two-point Dixon with bipolar readouts can have reduced quality due to gradient errors.

Goal(s): To develop improved imaging capabilities by leveraging gradient impulse response function (GIRF) measurements to correct for gradient errors and yield better image quality.

Approach: A radial two-point Dixon acquisition was compared using GIRF-corrected and uncorrected reconstructions in phantoms and a human volunteer.

Results: The use of GIRF in the reconstruction of two-point Dixon radial imaging provides improved image quality and better fat-water separation and provided similar quality to a Cartesian acquisition.

Impact: This work demonstrates improved image quality and improved fat-water separation by incorporating gradient impulse response function compensation in two-point Dixon radial imaging for an intended application of motion-robust whole body MR imaging.

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