Two-dimensional Gaussian regression for sub-pixel displacement estimation in particle image velocimetry or particle position estimation in particle tracking velocimetry

2005 ◽  
Vol 38 (4) ◽  
pp. 511-515 ◽  
Author(s):  
H. Nobach ◽  
M. Honkanen
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
Particle Image ◽  
Position Estimation ◽  
Two Dimensional ◽  
Displacement Estimation ◽  
Particle Position ◽  
Image Velocimetry ◽  
Gaussian Regression

scholarly journals Optimized Time-Resolved Echo Particle Image Velocimetry– Particle Tracking Velocimetry Measurements Elucidate Blood Flow in Patients With Left Ventricular Thrombus

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Kaushik Sampath ◽  
Thura T. Harfi ◽  
Richard T. George ◽  
Joseph Katz
Keyword(s):  
Blood Flow ◽  
Particle Image Velocimetry ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
Particle Image ◽  
Left Ventricular ◽  
Time Resolved ◽  
Ventricular Thrombus ◽  
Image Velocimetry ◽  
Contrast Ultrasound

Contrast ultrasound is a widely used clinical tool to obtain real-time qualitative blood flow assessments in the heart, liver, etc. Echocardiographic particle image velocimetry (echo-PIV) is a technique for obtaining quantitative velocity maps from contrast ultrasound images. However, unlike optical particle image velocimetry (PIV), routine echo images are prone to nonuniform spatiotemporal variations in tracer distribution, making analysis difficult for standard PIV algorithms. This study introduces optimized procedures that integrate image enhancement, PIV, and particle tracking velocimetry (PTV) to obtain reliable time-resolved two-dimensional (2D) velocity distributions. During initial PIV analysis, multiple results are obtained by varying processing parameters. Optimization involving outlier removal and smoothing is used to select the correct vector. These results are used in a multiparameter PTV procedure. To demonstrate their clinical value, the procedures are implemented to obtain velocity and vorticity distributions over multiple cardiac cycles using images acquired from four left ventricular thrombus (LVT) patients. Phase-averaged data elucidate flow structure evolution over the cycle and are used to calculate penetration depth and strength of left ventricular (LV) vortices, as well as apical velocity induced by them. The present data are consistent with previous time-averaged results for the minimum vortex penetration depth associated with LVT occurrence. However, due to decay and fragmentation of LV vortices, as they migrate away from the mitral annulus, in two cases with high penetration, there is still poor washing near the resolved clot throughout the cycle. Hence, direct examination of entire flow evolution may be useful for assessing risk of LVT relapse before prescribing anticoagulants.

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