Vector Flow Research Articles

Validation of 2D flow MRI for helical and vortical flows

PurposeThe main objective of this study was to develop two-dimensional (2D) phase contrast (PC) methods to quantify the helicity and vorticity of blood flow in the aortic root.MethodsThis proof-of-concept study...

Prediction of Non-Stationary Multi-Head Cloud Motion Vectors for Intra-Hourly Satellite-Derived Solar Power Forecasting

Solar photovoltaic (PV) power has become one of the major renewable energy sources in modern power systems. Hence, solar forecasting is indispensable for addressing the uncertainties of PV power outputs. Since PV power generation mainly depends on solar radiation conditions, satellite-derived methods have been proven effective in large-scale short-term solar forecasting. These methods utilize satellite optical images to track cloud motion and do not require supplemental ground cameras. However, cloud motion between two consecutive satellite images is highly non-stationary, as the motion includes both displacement and shape variation. Conventional motion estimation methods may miss the detailed cloud variation information, increasing the errors in solar forecasting. In this study, a multi-head cloud motion vector prediction method is proposed to address this challenge. The method models cloud variation as the probabilistic sum of pixels moving under multiple optical flow vectors. Time-varying solar intensity is also considered in the method. In order to estimate these optical flow vectors, a learning-based intelligent model with a self-attention structure is established. The proposed method of multi-step-ahead satellite-derived solar forecasting is superior to conventional methods, as the results of case studies indicate that the proposed method improves the precision of intra-hourly PV power prediction.

First assessment of flow phenomena of acute and chronic thrombosis in the jugular veins using new ultrasound vector-flow imaging.

First assessment of flow changes in the jugular veins using high resolution ultrasound vector flow. 15 patients (8 males, 7 females) with an age range of 35 to 82 years (mean age 58.53±12.26 years) were examined by an experienced examiner using high power ultrasound equipment (Resona R9, Mindray) with probe technology (Mindray L9-3U Linear Array transducer, 2.5 to 9.0 MHz). This group was compared with five healthy subjects (mean age 35.4±13.79 years) as a reference. To assess flow changes, the color-coded duplex sonography and the novel vector flow technique were used. The evaluation was performed of vector morphology changes, turbulence, and wall resistance measurements. There were changes after acute and chronic thrombosis in 9 cases, and venous compression in 7 cases. Turbulence was measurable from 0.01 % to 64.44 %, the average turbulence was 19.73±22.06 %. Wall resistance measurement showed values from 0.01 Pa to 3.14 Pa, depending on the age of the thrombosis or compression. The reference veins showed turbulence of 0.94±1.5 % and a mean wall resistance of 0.05±0.05 Pa. There are statistically significant differences between normal and thrombotic or compressed veins in terms of maximum wall stress (p = 0.006) and mean degree of turbulence (p = 0.012), while the difference in mean wall stress is not statistically significant (p = 0.058). Despite still existing technical limitations, the combination of V-flow and wall stress measurements in jugular vein changes suggests a high diagnostic potential.

Error Analysis and Condition Estimation of the Pyramidal Form of the Lucas-Kanade Method in Optical Flow

Optical flow is the apparent motion of the brightness patterns in an image. The pyramidal form of the Lucas-Kanade (LK) method is frequently used for its computation but experiments have shown that the method has deficiencies. Problems arise because of numerical issues in the least squares (LS) problem minAx−b22, A∈Rm×2 and m≫2, which must be solved many times. Numerical properties of the solution x0=A†b = (ATA)−1ATb of the LS problem are considered and it is shown that the property m≫2 has implications for the error and stability of x0. In particular, it can be assumed that b has components that lie in the column space (range) R(A) of A, and the space that is orthogonal to R(A), from which it follows that the upper bound of the condition number of x0 is inversely proportional to cosθ, where θ is the angle between b and its component that lies in R(A). It is shown that the maximum values of this condition number, other condition numbers and the errors in the solutions of the LS problems increase as the pyramid is descended from the top level (coarsest image) to the base (finest image), such that the optical flow computed at the base of the pyramid may be computationally unreliable. The extension of these results to the problem of total least squares is addressed by considering the stability of the optical flow vectors when there are errors in A and b. Examples of the computation of the optical flow demonstrate the theoretical results, and the implications of these results for extended forms of the LK method are discussed.

Interaction mechanism between cloud cavitation and micro vortex flows

Micro vortex generators (micro-VGs) could affect cavitation, but the control mechanism is not yet fully understood. Simulating and analyzing the effect of micro vortex generators (micro-VGs) on cloud cavitation is crucial as it can help in suppressing the collapse of cavitation clouds, which is beneficial for marine machinery. In this work, micro-VGs were installed parallel to the initiation of the attached cavity on a NACA0015 hydrofoil. A compressible simulation method was used to obtain the cavitating flows around both the smooth hydrofoil and the one with micro-VGs. Subsequently, the generation of micro vortex flows and the effect of micro-VGs on transient evolution of cloud cavitation were analyzed. The results indicate that the installation of triangular micro vortex generators alters the flow vectors around them, inducing micro vortex flows with opposite rotational directions behind adjacent vortex generators. These vortex generators potentially affect cavitation on the hydrofoil by modifying pressure distribution, vortex structures, and turbulent kinetic energy. Under the specified cloud cavitation operating condition, the shedding and collapse of clouds on the smooth hydrofoil are replaced by the partial separation and collapse of sheet cavitation on the hydrofoil with micro-VGs. Despite a minor loss in time-averaged lift, the lift-to-drag ratio is improved, and the stability of the flow field is enhanced. After installing micro-VGs, the pressure fluctuation is primarily caused by the partial collapse and separation of sheet cavitation. Installing micro VGs at the hydrofoil's leading edge suppresses pressure pulsation.

Perceptual transitions between object rigidity and non-rigidity: Competition and cooperation among motion energy, feature tracking, and shape-based priors.

Why do moving objects appear rigid when projected retinal images are deformed non-rigidly? We used rotating rigid objects that can appear rigid or non-rigid to test whether shape features contribute to rigidity perception. When two circular rings were rigidly linked at an angle and jointly rotated at moderate speeds, observers reported that the rings wobbled and were not linked rigidly, but rigid rotation was reported at slow speeds. When gaps, paint, or vertices were added, the rings appeared rigidly rotating even at moderate speeds. At high speeds, all configurations appeared non-rigid. Salient features thus contribute to rigidity at slow and moderate speeds but not at high speeds. Simulated responses of arrays of motion-energy cells showed that motion flow vectors are predominantly orthogonal to the contours of the rings, not parallel to the rotation direction. A convolutional neural network trained to distinguish flow patterns for wobbling versus rotation gave a high probability of wobbling for the motion-energy flows. However, the convolutional neural network gave high probabilities of rotation for motion flows generated by tracking features with arrays of MT pattern-motion cells and corner detectors. In addition, circular rings can appear to spin and roll despite the absence of any sensory evidence, and this illusion is prevented by vertices, gaps, and painted segments, showing the effects of rotational symmetry and shape. Combining convolutional neural network outputs that give greater weight to motion energy at fast speeds and to feature tracking at slow speeds, with the shape-based priors for wobbling and rolling, explained rigid and non-rigid percepts across shapes and speeds (R2 = 0.95). The results demonstrate how cooperation and competition between different neuronal classes lead to specific states of visual perception and to transitions between the states.

Application Research of Vector Flow Technique on Convex Array Ultrasonic Probe of Abdomen

Vector flow imaging (VFI) is an innovative ultrasound flow measurement technology. Compared with the traditional color Doppler and spectral Doppler, VFI has the advantages of independence of angle correction and direct acquisition of real-time amplitude and direction of flow. Transverse oscillation (TO) method is one of the effective methods for vector flow imaging. However, a complete and detailed algorithm validation process based on commercial ultrasound machines is still lacking due to more complex convex probes. This study starts with introducing the imaging process and principle of transverse oscillation vector flow technique, and calculates the error between the set velocity value and the measured velocity value through the simulation experiment, and verifies the error between the set velocity value and the measured velocity value through the Doppler flow phantom experiment. Among them, the velocity value measured by the TO vector flow technique in the simulation experiment is 0.48 m/s and the preset value is 0.50 m/s, the error between them is -4%. The velocity values are 8.33, 11.14, 14.44 and 16.67 cm/s measured by the Doppler flow phantom experiment, the actual velocity values are 7.97, 10.78, 14.06 and 17.34 cm/s, the errors between them are all within ±5%. Both experiments verify the feasibility of using vector flow technique on abdominal convex probe.

Utility of vector flow mapping and [18F]fluorodeoxyglucose-positron emission tomography/computed tomography to assess left ventricular workload in obstructive hypertrophic cardiomyopathy.

Utility of vector flow mapping and [18F]fluorodeoxyglucose-positron emission tomography/computed tomography to assess left ventricular workload in obstructive hypertrophic cardiomyopathy.

Hemodynamic factors of spontaneous vertebral artery dissecting aneurysms assessed with numerical and deep learning algorithms: Role of blood pressure and asymmetry

Background and ObjectivesThe pathophysiology of spontaneous vertebral artery dissecting aneurysms (SVADA) is poorly understood. Our goal is to investigate the hemodynamic factors contributing to their formation using computational fluid dynamics (CFD) and deep learning algorithms. MethodsWe have developed software that can use patient imagery as input to recreate the vertebrobasilar arterial system, both with and without SVADA, which we used in a series of three patients. To obtain the kinematic blood flow data before and after the aneurysm forms, we utilized numerical methods to solve the complex Navier-Stokes partial differential equations. This was accomplished through the application of a finite volume solver (OpenFoam/Helyx OS). Additionally, we trained a neural ordinary differential equation (NODE) to learn and replicate the dynamical streamlines obtained from the computational fluid dynamics (CFD) simulations. ResultsIn all three cases, we observed that the equilibrium of blood pressure distributions across the VAs, at a specific vertical level, accurately predicted the future SVADA location. In the two cases where there was a dominant VA, the dissection occurred on the dominant artery where blood pressure was lower compared to the contralateral side. The SVADA sac was characterized by reduced wall shear stress (WSS) and decreased velocity magnitude related to increased turbulence. The presence of a high WSS gradient at the boundary of the SVADA may explain its extension. Streamlines generated by CFD were learned with a neural ordinary differential equation (NODE) capable of capturing the system’s dynamics to output meaningful predictions of the flow vector field upon aneurysm formation. ConclusionIn our series, asymmetry in the vertebrobasilar blood pressure distributions at and proximal to the site of the future SVADA accurately predicted its location in all patients. Deep learning algorithms can be trained to model blood flow patterns within biological systems, offering an alternative to the computationally intensive CFD. This technology has the potential to find practical applications in clinical settings.

Evaluation of Turbulence Index and Flow Pattern for Atherosclerotic Carotid Stenosis: A High-Frame-Rate Vector Flow Imaging Study

ObjectiveThe emerging high-frame rate vector flow imaging (H-FRV Flow) provides a new way of hemodynamic evaluation for complex blood flow. This study aimed to explore quantitatively the characteristics of complex flow with turbulence (Tur) index and analyze flow pattern in atherosclerotic internal carotid artery stenosis (ICAS) using H-FRV Flow. MethodsThis study prospectively included 60 patients with ICAS. Tur values in different segments of stenosis and cardiac phases were compared. Meanwhile Spearman correlation analysis was performed between clinical plaque characteristics with turbulence grading by ln (Tur). Three complex flow patterns were qualitatively drawn on vector flow mode, and the detection rate of flow patterns in different stenosis groups and ulceration groups were compared. ResultsHighly disordered blood flow was observed in the stenosis (Tur (%) (M, QR) =12.5, 21.5) and distal segment (15.4, 27.2), particularly during systole (21.0, 30.7/ 33.3, 38.7, P<0.05). Spearman correlation analysis showed that stenosis rate was correlated with turbulence grading in the stenosis (ρ=0.65, P<0.05) and distal segment (ρ=0.79, P<0.05), and ulcer formation was correlated with turbulence grading in the stenosis segment (ρ=0.58, P<0.05). The overall detection rate of three flow patterns was higher respectively in the severe stenosis group (22/22) versus mild to moderate stenosis group (21/38) (P<0.001) and the ulcer group (21/23) versus non-ulcer group (23/37) (P<0.001). ConclusionH-FRV Flow was helpful for assess the severity and characteristics of flow turbulence. Lumen geometric factors could affect the flow turbulence and blood flow patterns around the plaque. This would provide important hemodynamic information for the detection of high-risk plaque.

Pseudorapidity dependence of anisotropic flow and its decorrelations using long-range multiparticle correlations in Pb–Pb and Xe–Xe collisions

The pseudorapidity dependence of elliptic (v2), triangular (v3), and quadrangular (v4) flow coefficients of charged particles measured in Pb–Pb collisions at a centre-of-mass energy per nucleon pair of sNN=5.02TeV and in Xe–Xe collisions at sNN=5.44TeV with ALICE at the LHC are presented. The measurements are performed in the pseudorapidity range −3.5<η<5 for various centrality intervals using two- and multi-particle cumulants with the subevent method. The flow probability density function (p.d.f.) is studied with the ratio of flow coefficient v2 calculated with four- and two-particle cumulant, and suggests that the variance of flow p.d.f. is independent of pseudorapidity. The decorrelation of the flow vector in the longitudinal direction is probed using two-particle correlations. The results measured with respect to different reference regions in pseudorapidity exhibit differences, argued to be a result of saturating decorrelation effect above a certain pseudorapidity separation, in contrast to previous publications which assign this observation to non-flow effects. The results are compared to 3+1 dimensional hydrodynamic and the AMPT transport model calculations. Neither of the models is able to simultaneously describe the pseudorapidity dependence of measurements of anisotropic flow and its fluctuations. The results presented in this work highlight shortcomings in our current understanding of initial conditions and subsequent system expansion in the longitudinal direction. Therefore, they provide input for its improvement.

Excitation time imaging condition reverse time migration based on physics-informed neural network traveltime calculation with wavefield decomposition using optical flow vector

Abstract Although the excitation-time imaging condition offers a lower memory consumption and higher computational efficiency compared to cross-correlation imaging condition, it has not been widely used in industrial applications because of the accuracy problem of traveltime calculation and the influence of low-wave-number noise. In this paper, we introduce the physics-informed neural network (PINN) algorithm to achieve a high-precision traveltime calculation of the source forward wavefield. Subsequently, we introduce a technique for high-precision wavefield decomposition of the reverse-time wavefield via the optical flow vector, enabling us to realize a correlation-weighted stacking imaging of each wavefield. Model experiments and real data processing show that the proposed traveltime calculation algorithm based on PINN offers high accuracy and good applicability in the excitation time reverse-time migration imaging of complex models, and correlation-weighted stacking imaging based on optical flow vector-based wavefield separation can significantly suppress the noise with low wavenumber and achieve high-precision imaging of complex models.

Automated optic disk segmentation for optic disk edema classification using factorized gradient vector flow

One significant ocular symptom of neuro-ophthalmic disorders of the optic disk (OD) is optic disk edema (ODE). The etiologies of ODE are broad, with various symptoms and effects. Early detection of ODE can prevent potential vision loss and fatal vision problems. The texture of edematous OD significantly differs from the non-edematous OD in retinal images. As a result, techniques that usually work for non-edematous cases may not work well for edematous cases. We propose a fully automatic OD classification of edematous and non-edematous OD on fundus image collections containing a mixture of edematous and non-edematous ODs. The proposed algorithm involved localization, segmentation, and classification of edematous and non-edematous OD. The factorized gradient vector flow (FGVF) was used to segment the ODs. The OD type was classified using a linear support vector machine (SVM) based on 27 features extracted from the vessels, GLCM, color, and intensity line profile. The proposed method was tested on 295 images with 146 edematous cases and 149 non-edematous cases from three datasets. The segmentation achieves an average precision of 88.41%, recall of 89.35%, and F1-Score of 86.53%. The average classification accuracy is 99.40% and outperforms the state-of-the-art method by 3.43%.

Damping oscillations of a cylinder with a coaxial disc and a stabilizer

The damped rotational oscillations of the cylinder, which is equipped with a coaxial disk in the head part, and has a stabilizer in the tail part, are studied. The elongation of the cylinder (the ratio of length to diameter) is nine. The cylinder is mounted in the test section of the low velocities wind tunnel with a wire suspension containing steel springs. In the equilibrium position, the axis of the cylinder is horizontal and parallel to the velocity vector of the incoming flow. Under the action of the air flow, the attenuation of rotational oscillations of the cylinder changes. A semiconductor strain gauge is attached to one of the suspension springs, which measures the dependence of spring tension on time during oscillations. The voltage at the output of the strain gauge is transmitted to the PC oscilloscope. The digital signal of the oscilloscope is transmitted to the computer. After calibration of the device, the frequency and amplitude of damped rotational oscillations around a horizontal axis passing through the center of the cylinder and perpendicular to the velocity vector of the incoming flow are determined. The effect of the air flow is described by analogues of rotational derivatives, which in the case of bluff bodies depend on the amplitude of the oscillations of the angle of inclination of the body and on the amplitude of the angular velocity. A simple model of the stabilizer’s effect on rotational derivatives is proposed.

Geography of population migration of the Southern Federal District

The article, based on state statistics, conducted a study of the transformation of geography and trends in the development of migration of the population of the Southern Federal District. Using an interdisciplinary integrated approach, an analysis of migration flows, their directions, scale and intensity was carried out, the geography of migrations of the most migratoryly attractive subject of the district - Krasnodar Territory - was determined, and mapping of migration indicators was carried out using modern information technologies for studying space and visualization.It is shown that, despite the decrease in migration turnover due to the coronavirus pandemic, the long- term trend of positive migration dynamics in the Southern Federal District has remained, and in terms of the intensity of net migration in 2021, the macroregion took first place among all Russian districts.There have been no major changes in the geography of incoming and outgoing migration flows. Intra- Russian migration is characterized by a migration outflow of the population to the Central and Northwestern federal districts, and migrants from all other districts, but most of all from Siberia and the Far East, come to the southern macroregion. The main flows of international migrants come from citizens of the CIS countries, primarily from Ukraine, Armenia, Kazakhstan, Tajikistan, Uzbekistan, and Azerbaijan.A comparative analysis of the migration movement of the subjects of the Southern Federal District showed that in the macroregion Krasnodar Territory ranks first in terms of the volume and effectiveness of migration, and in terms of the intensity of migration movement, it exceeds the Russian average. To date, the steady trend of positive dynamics in the migration balance that has developed in Kuban since the middle of the last century has been preserved. However, there has been a significant decline in net migration. The main modern vector of intra-Russian migration flows is movement to Kuban from the northern regions of Russia, Siberia and the Far East. Most international migrants arrived in the Krasnodar region from CIS countries. During the study period, the main suppliers of cross-border migrants were Ukraine, Armenia and Kazakhstan.

Integrating ecosystem and contaminant models to predict the effects of ecosystem fluxes on contaminant dynamics

AbstractEnvironmental contamination is one of the major drivers of ecosystem change in the Anthropocene. Toxic chemicals are not constrained to their source of origin as they cross ecosystem boundaries via biotic (e.g., animal migration) and abiotic (e.g., water flow) vectors. Meta‐ecology has led to important insights on how spatial flows or subsidies of matter across ecosystem boundaries can have broad impacts on local and regional ecosystem dynamics but has not yet addressed the dynamics of pollutants in recipient ecosystems. Incorporating meta‐ecosystem processes (i.e., flux of materials across ecosystem boundaries) into contaminant dynamics can elucidate how contaminants may reverberate among local food chains. Here, we derive a modeling framework to predict how spatial ecosystem fluxes can influence contaminant dynamics and how this influence is dependent on the type of ecosystem flux (e.g., herbivore movement vs. abiotic chemical flows). We mix an analytical and numerical approach to analyze our integrative model which couples two subcomponents that have previously been studied independently of each other—an ecosystem model and a contaminant model. We observe an array of dynamics for how chemical concentrations change with increasing nutrient input and loss rate across trophic levels. When we tailor our range of chemical parameter values (e.g., environmental uptake of contaminant and assimilation efficiency of the contaminant) to specific organic chemicals, our results demonstrate that increasing nutrient input rates can lead to trophic dilution in pollutants such as polychlorinated biphenyls across trophic levels. However, increasing nutrient loss rate causes an increase in the concentrations of chemicals across all trophic levels. A sensitivity analysis demonstrates that nutrient recycling is an important ecosystem process impacting contaminant concentrations, generating predictions to be addressed by future empirical studies. Importantly, our model demonstrates the utility of our framework for identifying drivers of contaminant dynamics in connected ecosystems including the importance that (1) ecosystem processes and (2) movement, especially movement of lower trophic levels, have on contaminant concentrations.

Physics-Guided Neural Networks for Intraventricular Vector Flow Mapping.

Intraventricular vector flow mapping (iVFM) seeks to enhance and quantify color Doppler in cardiac imaging. In this study, we propose novel alternatives to the traditional iVFM optimization scheme by utilizing physics-informed neural networks (PINNs) and a physics-guided nnU-Net-based supervised approach. When evaluated on simulated color Doppler images derived from a patient-specific computational fluid dynamics model and in vivo Doppler acquisitions, both approaches demonstrate comparable reconstruction performance to the original iVFM algorithm. The efficiency of PINNs is boosted through dual-stage optimization and pre-optimized weights. On the other hand, the nnU-Net method excels in generalizability and real-time capabilities. Notably, nnU-Net shows superior robustness on sparse and truncated Doppler data while maintaining independence from explicit boundary conditions. Overall, our results highlight the effectiveness of these methods in reconstructing intraventricular vector blood flow. The study also suggests potential applications of PINNs in ultrafast color Doppler imaging and the incorporation of fluid dynamics equations to derive biomarkers for cardiovascular diseases based on blood flow.

The Difference of Mean WSS Value on The Carotid Bifurcation and The Medial Segment of Common Carotid Artery Using Vector Flow Ultrasonography in Hypertensive Patients at Prof Dr. I.G.N.G Ngoerah General Hospital February-April 2022

Background : Hypertension is a risk factor for atherosclerosis which increases the risk of stroke. Transitions in blood vessels such as bifurcations are associated with changes in the velocity and pattern of blood flow that decrease wall shear stress (WSS) and is believed to be a risk factor for atherosclerosis. Shear stress on the common carotid artery also decreased with increasing blood pressure. This study aims to determine the difference of mean WSS value on the carotid bifurcation and the medial segment of common carotid artery using vector flow ultrasonography in hypertensive patients. Methods: This study used a cross-sectional design with the research location at the Radiology Installation of Prof. Dr. I.G.N.G Ngoerah Hospital Denpasar in February-April 2022. The sample of this study was hypertensive patients who came to the Radiology Installation of Prof. Dr. I.G.N.G Ngoerah Hospital and met the inclusion criteria as many as 32 people. The examination was carried out by a consultant of head and neck radiology, using an ultrasound device with a linear transducer probe that has a probe frequency range of 3-9 Mhz. Results: The average age of the sample in this study was 50 years, with 9 males (28.1%), 23 females (71.9%). The results showed that the average maximum WSS value on the carotid bifurcation (3.37±0.96) Pa, the mean value (1.15±0.45) Pa, while the average maximum WSS value on the medial segment of the common carotid artery (4 ,41±1.45)Pa, the mean value (1.78±0.54)Pa. The average maximal and mean WSS value on carotid bifurcation were lower than the medial segment of the common carotid artery in hypertensive patients (p&lt;0,05). The results of multivariate analysis on WSS values after controlling for confounding variables, obtained the average maximal and mean WSS value on carotid bifurcation, remained lower than the medial segment of the common carotid artery (p&lt;0,05). Conclusion: there were significant differences in the mean wall shear stress (WSS) of the carotid bifurcation and the medial segment of the common carotid artery in hypertensive patients. Suggestions that can be done next are in facilities that have vector flow ultrasonography facilities, it is recommended to measure the WSS value in hypertensive patients as additional information as a predictor of atherosclerosis

Bioinspired Fiber-Optic Vector Flow Sensor Based on Enhanced Vernier Effect for Marine Sensing

Bioinspired Fiber-Optic Vector Flow Sensor Based on Enhanced Vernier Effect for Marine Sensing

Increasing the Maximum Detectable Flow Velocity in High-Frequency Ultrasound Vector Doppler Imaging.

High-frequency ultrasound (HFUS; >30 MHz) Doppler imaging has been widely used in the imaging of small animals and humans because of its high resolution. Vector Doppler imaging (VDI) has certain advantages for visualizing complex flow patterns independent of the Doppler angle. However, no commercial HFUS VDI system is currently available; therefore, several studies have connected an ultrasound research platform (Verasonics Vantage 256) with an HFUS array transducer for HFUS VDI. Unfortunately, the maximum frame rate of this system is only 10 kHz at an operational frequency of 40 MHz because of limitations related to data transmission hardware, thereby restricting the maximum detectable velocity of Doppler measurements. To address this drawback, in the present study, an electrocardiography (ECG)-gating-based HFUS VDI system was developed to avoid Doppler flow aliasing in data acquisition by ultrasound research platform at its maximum frame rate of 10 kHz. The developed method aligns all tilted plane waves with the ECG R-wave, which avoids the trade-off between frame rate and tilted angles number in conventional VDI. The performance of the proposed data acquisition method in HFUS VDI was verified using a steady-flow phantom, for which estimation errors were less than 10% under different flow settings. In animal studies, peak flow velocities in the carotid artery, left ventricle, and aortic arch of wild-type mice were measured (approximately 55, 655, and 765 mm/s, respectively). Also, the HFUS VDI from the mitral regurgitation mice model was obtained to present the complex flow patterns through the proposed method. In contrast to the conventional method, no Doppler aliasing occurs in the proposed method because the frame rate is sufficient. The experimental results indicate the developed HFUS VDI has the potential to become a useful tool for vector flow visualization in small animals, even under a high flow velocity.