A fully automated algorithm for estimating tissue motion and strain from 2-D cine DENSE MRI showed good agreement with the standard semi-manual analysis method in simulated and human data.
Does a fully automated motion estimation algorithm for 2-D cine DENSE MRI provide comparable results to standard semi-manual analysis?
A novel fully automated algorithm for estimating tissue motion and strain from 2-D cine DENSE MRI shows good agreement with standard semi-manual methods, potentially improving measurement throughput and simplifying data interpretation.
Cine displacement encoding with stimulated echoes (DENSE) is a magnetic resonance (MR) method that directly encodes tissue displacement into MR phase images. This technique has successfully interrogated many forms of tissue motion, but is most commonly used to evaluate cardiac mechanics. Currently, motion analysis from cine DENSE images requires manually delineated anatomical structures. An automated analysis would improve measurement throughput, simplify data interpretation, and potentially access important physiological information during the MR exam. In this paper, we present the first fully automated solution for the estimation of tissue motion and strain from 2-D cine DENSE data. Results using both simulated and human cardiac cine DENSE data indicate good agreement between the automated algorithm and the standard semi-manual analysis method.
Gilliam et al. (Tue,) conducted a other in Cardiac mechanics. Fully automated algorithm for tissue motion and strain estimation vs. Standard semi-manual analysis method was evaluated on Agreement between automated algorithm and standard semi-manual analysis. A fully automated algorithm for estimating tissue motion and strain from 2-D cine DENSE MRI showed good agreement with the standard semi-manual analysis method in simulated and human data.
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