Adaptive dynamic grid interpolation: A robust, high-performance displacement smoothing filter for myocardial strain imaging

Accurately assessing local myocardial strain is important for diagnosing ischemic heart diseases because decreased myocardial motion often appears in the early stage. The abnormal contraction motion can be visualized by myocardial strain images, but the strain calculation is very sensitive to noise. In our previous research, we proposed a dynamic grid-interpolation method for overcoming the limitation of the trade-off between spatial resolution and accuracy in traditional moving-average filters. Here, we propose a novel adaptive dynamic grid-interpolation method with the ability to adjust smoothing adaptively for myocardial strain imaging. In a model with the infarcted region located around 1 to 3 o'clock, the accuracy was improved from 41.47% to 22.90% without degrading spatial resolution compared to that generated by using median and moving averaging filters, even for a low SNR.