Meeting Banner
Abstract #2339

Iterative Model-Based Image Reconstruction of RF gradient-based MRI

Taylor Froelich1 and Michael Garwood1
1Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, MN, United States


When reconstructing with traditional Fourier-based techniques, image distortions arising from nonlinear B1 and B0 inhomogeneity can plague radiofrequency-based (RF) imaging methods that rely on B1 gradients for spatial encoding. In this work, we propose a new framework for reconstructing multi-dimensional RF gradient-based images leveraging an iterative approach to solve a regularized inverse problem. The proposed methodology employs a full Bloch simulation to reconstruct an undistorted image after determination of the forward operator and measured receive coil sensitivities.

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

Join Here