Meeting Banner
Abstract #0303

Assessment of resolution and noise in MR images reconstructed by data driven approaches

Katja Lauer1,2, Jonas Kleineisel1, Alfio Borzì2, Thorsten Alexander Bley1, Herbert Köstler1, and Tobias Wech1
1Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany, 2Institute of Mathematics, University of Würzburg, Würzburg, Germany


Data-driven reconstruction of undersampled raw data has gained more and more importance in recent years. Due to the non-linear and non-stationary transform characteristics of these imaging methods, objective image quality assessment is difficult. We propose a heuristic approach based on local point spread functions and multiple replica reconstructions, to enable the derivation of resolution- and g-factor-maps for individual images. The method is exemplarily applied in T1- and T2-weighted images of the brain, using a UNet and a Variational Network trained with data from the fastMRI project.

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

Join Here