Abstract
We present quantitative comparisons of three categories of velocity estimation algorithms including centroid techniques (adaptive centroid technique and weighted centroid technique), sliding-window filtering technique, and correlation techniques (autocorrelation and cross-correlation). We introduce, among these five algorithms, two new algorithms: weighted centroid and sliding- window filtering. Simulations and in vivo blood flow data are used to assess the velocity estimation accuracies of these algorithms. The comparison demonstrates that the sliding-window filtering technique is superior to the other techniques in terms of velocity estimation accuracy and robustness to noise.
© 2002 Optical Society of America
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