Meeting Banner
Abstract #3633

Suppression of Artifact-Generating Echoes in Cine DENSE using Deep Learning

Mohammad Abdishektaei1, Xue Feng1, Craig H Meyer1, and Frederick H Epstein1
1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States

Cine displacement encoding with stimulated echoes (DENSE) is an accurate and reproducible method of strain imaging. The stimulated echo (STE), which carries the tissue displacement information in it’s phase, is simultaneously acquired with two artifact-generating echoes. A combination of phase-cycled acquisitions and through-plane dephasing are typically used to suppress the artifact-generating echoes. The limitations of these methods are longer acquisition times, susceptibility to breathing motion and the loss of signal-to-noise ratio due to intravoxel dephasing. To potentially overcome these limitations, the use of a deep convolutional neural network to suppress the undesired echoes from a single acquisition was investigated.

This abstract and the presentation materials are available to 2020 meeting attendees and eLibrary customers only; a login is required.

Join Here