Yu Wang1, Sona Ghadimi1, Changyu Sun1, and Frederick H. Epstein1,2
1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, 2Radiology, University of Virginia, Charlottesville, VA, United States
1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, 2Radiology, University of Virginia, Charlottesville, VA, United States
A DENSE-trained deep network with through-time correction is a promising
new method to predict intramyocardial motion from contour motion.
Figure 1: Overall
concept of using DL of DENSE datasets to predict intramyocardial displacement
from contour motion. (A) Training of FlowNet2 using DENSE data, and (B)
addition of a through-time correction network.
Figure 4: Example myocardial displacement
movies for FlowNet2, DT-FlowNet2, TC-DT-FlowNet2 and DENSE ground truth.