Quantitative assessment of flow velocity-estimation algorithms for optical Doppler tomography imaging.
We present a quantitative comparison of three categories of velocity estimation algorithms, including centroid techniques (the adaptive centroid technique and the weighted centroid technique), the 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. These comparisons demonstrate that the sliding-window filtering technique is superior to the other techniques in terms of velocity estimation accuracy and robustness to noise.
Piao
Daqing
D
Department of Electrical and Computer Engineering, University of Connecticut, Storrs 06269-2157, USA. piao@engr.uconn.edu
Otis
Linda L
LL
Dutta
Niloy K
NK
Zhu
Quing
Q
D000465:Algorithms; D003198:Computer Simulation; D014054:Tomography; D018608:Ultrasonography, Doppler