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Abstract #2225

Myocardial Segmentation and Phase Unwrapping for Automatic Analysis of DENSE Cardiac MRI using Deep Learning

Sona Ghadimi1, Xue Feng1, Craig H. Meyer1, and Frederick H. Epstein1
1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States

DENSE myocardial strain imaging is a method wherein tissue displacement is encoded in the image phase. Myocardial segmentation and phase unwrapping are two key steps in quantitative displacement and strain analysis of DENSE images. Prior DENSE analysis methods for segmentation and phase unwrapping were semi-automated techniques, requiring user intervention. In this study, we developed deep learning (DL) methods for fully automated myocardial segmentation and phase unwrapping for short-axis DENSE images. Quantitative and qualitative evaluations show promising results for the proposed DL-based segmentation and phase unwrapping methods, eliminating all manual steps needed for fully automatic DENSE strain analysis.

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