The spatio-temporal elastic registration algorithm accurately estimated cardiac motion from 2D echocardiograms, demonstrating significant differences in systolic displacement and strain between normal, hypokinetic, and akinetic segments (p<0.001).
Observational (n=12)
Does a spatio-temporal elastic registration algorithm improve the accuracy of cardiac motion estimation from ultrasound sequences compared to pairwise registration?
A novel spatio-temporal elastic registration algorithm improves cardiac motion estimation from ultrasound images by introducing temporal consistency, successfully differentiating normal from pathological left ventricular segments.
valor p: p=<0.001
We propose a new spatio-temporal elastic registration algorithm for motion reconstruction from a series of images. The specific application is to estimate displacement fields from two-dimensional ultrasound sequences of the heart. The basic idea is to find a spatio-temporal deformation field that effectively compensates for the motion by minimizing a difference with respect to a reference frame. The key feature of our method is the use of a semi-local spatio-temporal parametric model for the deformation using splines, and the reformulation of the registration task as a global optimization problem. The scale of the spline model controls the smoothness of the displacement field. Our algorithm uses a multiresolution optimization strategy to obtain a higher speed and robustness. We evaluated the accuracy of our algorithm using a synthetic sequence generated with an ultrasound simulation package, together with a realistic cardiac motion model. We compared our new global multiframe approach with a previous method based on pairwise registration of consecutive frames to demonstrate the benefits of introducing temporal consistency. Finally, we applied the algorithm to the regional analysis of the left ventricle. Displacement and strain parameters were evaluated showing significant differences between the normal and pathological segments, thereby illustrating the clinical applicability of our method.
Ledesma‐Carbayo et al. (Tue,) conducted a observational in Myocardial wall motion abnormalities (prior myocardial infarction) (n=12). Spatio-temporal elastic registration algorithm vs. Consecutive elastic registration / Expert qualitative scoring was evaluated on Mean displacement vector and mean local deformation (strain) of myocardial segments during systole (p=<0.001). The spatio-temporal elastic registration algorithm accurately estimated cardiac motion from 2D echocardiograms, demonstrating significant differences in systolic displacement and strain between normal, hypokinetic, and akinetic segments (p<0.001).
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