A novel interpolation strategy for estimating subsample speckle motion

Multidimensional, high-resolution ultrasonic imaging of rapidly moving tiss ue is primarily limited by sparse sampling in the lateral dimension. In ord er to achieve acceptable spatial resolution and velocity quantization, inte rpolation of laterally sampled data is necessary. We present a novel method for estimating lateral subsample speckle motion and compare it with tradit ional interpolation methods. This method, called grid slopes, requires no a priori knowledge and can be applied to data with as few as two samples in the lateral dimension. Computer simulations were performed to compare grid slopes with two conventional interpolation schemes, parabolic fit and cubic spline. Results of computer simulations show that parabolic fit and cubic spline performed poorly at translations greater than 0.5 samples, and trans lations less than 0.5 samples were subject to an estimation bias. Grid slop es accurately estimated translations between 0 and 1 samples without estima tion bias at high signal-to-noise ratios. Given that the grid slopes interp olation technique performs well at high signal-to-noise ratios, one pertine nt clinical application might be tissue motion tracking.