title: Quantitative assessment of flow velocity-estimation algorithms for optical Doppler tomography imaging.
abstract: 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.
authors.affiliation: Department of Electrical and Computer Engineering, University of Connecticut, Storrs 06269-2157, USA. piao@engr.uconn.edu
authors.forename: Daqing
authors.initials: D
authors.lastname: Piao
authors.forename: Linda L
authors.initials: LL
authors.lastname: Otis
authors.forename: Niloy K
authors.initials: NK
authors.lastname: Dutta
authors.forename: Quing
authors.initials: Q
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D014054:Tomography; D018608:Ultrasonography, Doppler