An extended autocorrelation method for estimation of blood velocity

The conventional autocorrelation method (AM) to estimate the blood velocity for color flow imaging (CFI) is based on the phase estimation of the autocorrelation function. In this paper, a new extended autocorrelation method (EAM) that uses both phase and magnitude of the two dimensional (depth and temporal direction) autocorrelation function for estimating the blood velocity is presented. It is shown that the EAM has similar performance as the cross-correlation method (CCM). Both of them have smaller estimation variance than the AM and have the ability to estimate velocities beyond the Nyquist velocity, but the EAM is more computationally efficient than the CCM. A 2-D blood flow signal with rectilinear velocity including the transit time effect has also been simulated and the results are presented in this paper. For comparison, the EAM and the CCM have been applied to the simulated signals in which the flow velocities are up to four times the Nyquist velocity. The EAM has been further verified by experimental RF data from the subclavian artery     

Blood flow images by a SAW-based multigate Doppler system

Multigate operation of an ultrasound pulsed Doppler flowmeter, providing Doppler frequency detection in a number of adjacent sample volumes, is capable of displaying the instantaneous blood velocity distribution along the cross section of a sonified vessel. Real-time serial Doppler processing of 32 range cells has been implemented in a novel system using fast spectral analysis based on surface-acoustic wave (SAW) dispersive filters. The basic architecture and first in vitro experiments were reported previously. The in vivo application of the system is described here, and images of human carotid artery and jugular vein are presented. Appropriate display formats are introduced to use the great amount of information known on spatial and temporal behavior of flow profiles. Digital postprocessing of spectral Doppler data allows velocity profiles to be displayed at selected times to correlate spatial and temporal evolution. A color code can be used to represent different velocity strengths. The potential application of the system to two-dimensional (2-D) flow imaging is discussed.     

Spectral Doppler estimation utilizing 2-D spatial information and adaptive signal processing

The trade-off between temporal and spectral resolution in conventional pulsed wave (PW) Doppler may limit duplex/triplex quality and the depiction of rapid flow events. It is therefore desirable to reduce the required observation window (OW) of the Doppler signal while preserving the frequency resolution. This work investigates how the required observation time can be reduced by adaptive spectral estimation utilizing 2-D spatial information obtained by parallel receive beamforming. Four adaptive estimation techniques were investigated, the power spectral Capon (PSC) method, the amplitude and phase estimation (APES) technique, multiple signal classification (MUSIC), and a projection-based version of the Capon technique. By averaging radially and laterally, the required covariance matrix could successfully be estimated without temporal averaging. Useful PW spectra of high resolution and contrast could be generated from ensembles corresponding to those used in color flow imaging (CFI; OW = 10). For a given OW, the frequency resolution could be increased compared with the Welch approach, in cases in which the transit time was higher or comparable to the observation time. In such cases, using short or long pulses with unfocused or focused transmit, an increase in temporal resolution of up to 4 to 6 times could be obtained in in vivo examples. It was further shown that by using adaptive signal processing, velocity spectra may be generated without high-pass filtering the Doppler signal. With the proposed approach, spectra retrospectively calculated from CFI may become useful for unfocused as well as focused imaging. This application may provide new clinical information by inspection of velocity spectra simultaneously from several spatial locations.     

Optimal velocity estimation in ultrasound color flow imaging in presence of clutter

In color flow imaging (CFI), the rejection of tissue clutter signal is treated separately from blood velocity estimation by high-pass filtering the received Doppler signal. The complete suppression of clutter is then difficult to achieve without affecting the subsequent velocity estimates. In this work, a different approach to velocity estimation is investigated, based on a statistical model of the signal from both clutter and blood. An analytic expression for the Cramer-Rao lower bound (CRLB) is developed, and used to determine the existence of an efficient maximum likelihood estimator (MLE) of blood velocity in CFI when assuming full knowledge of the clutter statistics. We further simulate and compare the performance of the MLE to that of the autocorrelation method (ACM) using finite-impulse response (FIR) and polynomial regression clutter filters. Two signal scenarios are simulated, representing a central and peripheral vessel. Simulations showed that, by including 3-9 (independent) spatial points, the MLE variance approached the CRLB in both scenarios. The ACM was approximately unbiased only for the central scenario in the clutter filter pass band, then with a variance of up to four times the CRLB. The ACM suffered from a severe bias in the filter transition region, and a significant performance gain was achieved here using the MLE. For practical use, the clutter properties must be estimated. We finally replaced the known clutter statistics with an estimate obtained from low-rank approximations of the received sample correlation matrix. Used in the model-based framework, this method came close to the performance of the MLE, and it may be an important step toward a practical model-based estimator, including tissue clutter with optimal performance.     

Spatial and temporal dependence of single-pass parametric gain

Abstract

The use of focused Gaussian beams and short optical pulses to pump single-pass optical parametric amplifiers is examined. A simple model is introduced to mimic the experimental conditions used, and the expected intensity profile of the output signal for degenerate parametric amplification in LBO and MgO:LiNbO₃ is calculated. Experimental and theoretical results are compared for LBO. Second harmonic autocorrelation measurements were performed in order to determine the pulse duration of the output signal from the LBO parametric amplifier. These measurements showed that the amplified pulse was slightly shorter, and the deamplified pulse slightly longer, than the input signal—a result of the variation in the parametric gain over the 3 ps signal pulse. The implications of this spatial and temporal variation of the gain in squeezing are discussed.     

High resolution processing techniques for ultrasound doppler velocimetry in the presence of colored noise. Part II: Multiplephase pipe-flow velocity measurement

For pt.I see ibid., vol.50, no.3, p.267-78 (2003). This paper presents an application of continuous wave ultrasound Doppler velocity measurements to two-phase flow in pipes. In many petroleum wells, the multiphase flow is separated into two phases: the first is a liquid phase and the second is a gas phase with small scatterers. The problem of multiphase velocity profile measurements has not been satisfactorily solved by classical approaches due to the multiphase nature of the fluid and the presence of colored noise, which introduces a significant bias in classical frequency estimators. We propose the use of resolution frequency techniques to overcome the classical limitations. Direct estimation of Doppler frequency then obtained using either time frequency maximum frequency or arguments of poles of the parametric model that identifies the Doppler part of the signal is discussed. The tests made with synthetic Doppler signals and two-phase flow have demonstrated the excellent performance of the high resolution techniques based on reassignment and parametric techniques.     

Ultrasound simulation of complex flow velocity fields based on computational fluid dynamics

In this work, a simulation environment for the development of flow-related ultrasound algorithms is presented. Ultrasound simulations of realistic Doppler signals require accurate modeling of blood flow. Instead of using analytically described flow behavior, complex blood movement can be derived from velocity fields obtained with computational fluid dynamics (CFD). By further modeling blood as a collection of point scatterers, resulting RF-signals can be efficiently retrieved using an existing ultrasound simulation model. The main aim of this paper is to elaborate on creating CFD-based phantoms for ultrasound simulations. The coupling of a computed flow field with an ultrasound model offers flexible control of flow and ultrasound imaging parameters, beneficial for improving and developing imaging algorithms. The proposed method was validated in a straight tube with a stationary parabolic velocity profile and further demonstrated by an eccentrically stenosis carotid bifurcation. The estimated flow velocities are in good agreement with the CFD reference, both for color flow imaging and pulsed-wave doppler simulations. The presented method can also be extended to include wall mechanics simulations in future work.     

结合横向振荡和空间正交的向量血流速度测量

传统的彩色多普勒成像只能测量与超声波束平行的血流速度分量,且依赖于超声波束与血管之间的夹角。超声向量血流成像是一种更加先进的血流成像技术,该方法可以直接获得血流速度的实际大小和方向,因此不依赖于超声波束与血管之间的夹角。本文从向量血流测量方法之一的横向声场法入手,简要概括了横向振荡(Transverse Os‐cillation, TO)法和空间正交(Spatial Quadrature, SQ)法两种方法的基本原理、成像过程及各自的优缺点,并提出了一种互相结合的方法,即奇偶振荡法(Odd Even Oscillation, OEO),该方法利用 SQ法快速进行波束合成,利用 TO法计算最终的速度矢量,克服了 TO法和 SQ法各自的缺点,能够有效解决 TO法成像计算量大以及 SQ法出现混叠和对噪声灵敏度高的问题。     

Advances in Monitoring of Velocities and Densities of Particulates Using Microwave Doppler Effect

Recent advances in monitoring of velocities, densities, and mass flow rates of particulates using a microwave Doppler radar are presented. It has been found that the Doppler signal scattered by the flow field of particulates contains information not only about the mean velocity of the field (mean frequency of the Doppler signal) but also about the mean density of the field (rms value of the Doppler signal). Experimental results obtained using a X-band Doppler module are presented.     

Stable and unbiased flow turbulence estimation from pulse echo ultrasound

A new method for stable and unbiased flow turbulence estimation has been developed for medical ultrasonic color flow imaging. Conventional turbulence estimates from a finite number of transmitted pulses could be biased, unreliable, and erroneous. We found that a conventional method cannot provide quantitative estimates of variance of flow velocity. We propose a new approach for flow turbulence estimation that is based on analysis of the flow velocity vectors. The new method estimates the variance of the flow velocity and provides reliable estimates for flow turbulence. Numerical examples, computer simulations, and experiments using a flow phantom demonstrate that the new method can estimate variance of flow velocity accurately and without bias. This work also reports a complete derivation in the time domain for both unbiased velocity and turbulence estimations. The results include two velocity estimation equations agreeing with the 1-D and 2-D autocorrelation methods derived from the frequency domain. The results indicate that the new method for flow turbulence is particularly useful when the 2-D autocorrelation method is used for color flow imaging. The new method also appears to be able to detect low turbulence; therefore, it may be useful for diagnosing abnormalities such as minor stenoses and valvular jets.     

Multi-frequency encoding for fast color flow or quadroplex imaging

Ultrasonic color flow maps are made by estimating the velocities line by line over the region of interest. For each velocity estimate, multiple repetitions are needed. This sets a limit on the frame rate, which becomes increasingly severe when imaging deeper lying structures or when simultaneously acquiring spectrogram data for triplex imaging. This paper proposes a method for decreasing the data acquisition time by simultaneously sampling multiple lines for color flow maps, using narrow band signals with approximately disjoint spectral support. The signals are separated in the receiver by filters matched to the emitted waveforms, producing a number of data sets with different center frequencies. The autocorrelation estimator is then applied to each of the data sets. The method is presented, various side effects are considered, and the method is tested on data from a recirculating flow phantom. A mean standard deviation across the flow profile of 3.1, 2.5, and 2.1% of the peak velocity was found for bands at 5 MHz, 7 MHz, and 9 MHz, respectively. Alternatively, the method can be used for simultaneously sampling data for a color flow map and for multiple spectrograms using different spectral bands. Using three spectral bands, data for a color flow map and two independent spectrograms can be acquired at the time normally spent on acquiring data for a color flow map only. This yields an expansion of triplex imaging called multifrequency quadroplex imaging, which enables study of the flow over an arterial stenosis by simultaneously acquiring spectrograms on both sides of the stenosis, while maintaining the color flow map. The method was tested in vivo on data from the common carotid artery of a healthy male volunteer, both for fast color flow mapping and for multifrequency quadroplex imaging.     

A new time-domain narrowband velocity estimation technique for Doppler ultrasound flow imaging. II. Comparative performance assessment

For pt.I see ibid., vol.45, no.4, pp.939-54 (1998). The statistical performance of the new 2-D narrowband time-domain root-MUSIC blood velocity estimator described previously is evaluated using both simulated and flow phantom wideband (50% fractional bandwidth) ultrasonic data. Comparisons are made with the standard 1-D Kasai estimator and two other wideband strategies: the time domain correlator and the wideband point maximum likelihood estimator. A special case of the root-MUSIC, the "spatial" Kasai, is also considered. Simulation and flow phantom results indicate that the root-MUSIC blood velocity estimator displays a superior ability to reconstruct spatial blood velocity information under a wide range of operating conditions. The root-MUSIC mode velocity estimator can be extended to effectively remove the clutter component from the sample volume data. A bimodal velocity estimator is formed by processing the signal subspace spanned by the eigenvectors corresponding to the two largest eigenvalues of the Doppler correlation matrix. To test this scheme, in vivo common carotid flow complex Doppler data was obtained from a commercially available color flow imaging system. Velocity estimates were made using a reduced form of this data corresponding to higher frame rates. The extended root-MUSIC approach was found to produce superior results when compared to both 1- and 2-D Kasai-type estimators that used initialized clutter filters. The results obtained using simulated, flow phantom, and in vivo data suggest that increased sensitivity as well as effective clutter suppression can be achieved using the root-MUSIC technique, and this may be particularly important for wideband high frame rate imaging applications.     

A new high resolution color flow system using an eigendecomposition-based adaptive filter for clutter rejection

We present a new signal processing strategy for high frequency color flow mapping in moving tissue environments. A new application of an eigendecomposition-based clutter rejection filter is presented with modifications to deal with high blood-to-clutter ratios (BCR). Additionally, a new method for correcting blood velocity estimates with an estimated tissue motion profile is detailed. The performance of the clutter filter and velocity estimation strategies is quantified using a new swept-scan signal model. In vivo color flow images are presented to illustrate the potential of the system for mapping blood flow in the microcirculation with external tissue motion.     

A new high resolution color flow system using an eigendecomposition-based adaptive filter for clutter rejection

We present a new signal processing strategy for high frequency color flow mapping in moving tissue environments. A new application of an eigendecomposition-based clutter rejection filter is presented with modifications to deal with high blood-to-clutter ratios (BCR). Additionally, a new method for correcting blood velocity estimates with an estimated tissue motion profile is detailed. The performance of the clutter filter and velocity estimation strategies is quantified using a new swept-scan signal model. In vivo color flow images are presented to illustrate the potential of the system for mapping blood flow in the microcirculation with external tissue motion.     

Coded ultrasound for blood flow estimation using subband processing

This paper investigates the use of coded excitation for blood flow estimation in medical ultrasound. Traditional autocorrelation estimators use narrow-band excitation signals to provide sufficient signal-to-noise-ratio (SNR) and velocity estimation performance. In this paper, broadband coded signals are used to increase SNR, followed by subband processing. The received broadband signal is filtered using a set of narrow-band filters. Estimating the velocity in each of the bands and averaging the results yields better performance compared with what would be possible when transmitting a narrow-band pulse directly. Also, the spatial resolution of the narrow-band pulse would be too poor for brightness-mode (B-mode) imaging, and additional transmissions would be required to update the B-mode image. For the described approach in the paper, there is no need for additional transmissions, because the excitation signal is broadband and has good spatial resolution after pulse compression. This means that time can be saved by using the same data for B-mode imaging and blood flow estimation. Two different coding schemes are used in this paper, Barker codes and Golay codes. The performance of the codes for velocity estimation is compared with a conventional approach transmitting a narrow-band pulse. The study was carried out using an experimental ultrasound scanner and a commercial linear array 7 MHz transducer. A circulating flow rig was scanned with a beam-to-flow angle of 60 degrees. The flow in the rig was laminar and had a parabolic flow-profile with a peak velocity of 0.09 m/s. The mean relative standard deviation of the velocity estimate using the reference method with an 8-cycle excitation pulse at 7 MHz was 0.544% compared with the peak velocity in the rig. Two Barker codes were tested with a length of 5 and 13 bits, respectively. The corresponding mean relative standard deviations were 0.367% and 0.310%, respectively. For the Golay coded experiment, two 8-bit codes were used, and the mean relative standard deviation was 0.335%.     

Low-order AR models for mean and maximum frequency estimation in the context of Doppler color flow mapping

Autoregressive (AR) techniques are investigated by developing mean and maximum frequency estimators suitable for use in Doppler color flow mapping systems, where they are most needed. The estimators are based on low-order (for computational efficiency) AR models applied to complex signals whose real and imaginary parts are the in-phase and quadrature components of the analytical Doppler signal, respectively. A large number of simulated data sequences generated by a sinusoidal computer model and having different number of samples, spectral shapes, bandwidths, and signal-to-noise ratios are used to examine the performance (bias and variance) of the estimators in a systematic manner. Comparisons are made with the established autocorrelation technique, whose output is shown to be identical to one of the AR mean frequency estimators described.     

Experimental evaluation of velocity and power estimation forultrasound blood flow imaging, by means of a two-dimensionalautocorrelation approach

This paper evaluates experimentally the performance of a novel axial velocity estimator, the 2D autocorrelator, and its Doppler power estimation counterpart, the 2D zero-lag autocorrelator, in the context of ultrasound color flow mapping. The evaluation also encompasses the well-established 1D autocorrelation technique for velocity estimation and its corresponding power estimator (1D zero-lag autocorrelator), to allow performance comparisons under identical conditions. Clutter-suppressed in vitro data sets from a steady-flow system are used to document the effect of the range gate and ensemble length, noise level and angle of insonation on the precision of the velocity estimates. The same data sets are used to examine issues related to the estimation of the Doppler signal's power. The first-order statistics of power estimates from regions corresponding to flow and noise are determined experimentally and the ability of power-based thresholding to separate flow signals from noise is characterized by means of ROC analysis. In summary, the results of the in vitro evaluation show that the proposed 2D-autocorrelation form of processing is consistently better than the corresponding 1D-autocorrelation techniques, in terms of both velocity and power estimation. Therefore, given their relatively modest implementation requirements, the 2D-autocorrelation algorithms for velocity and power estimation appear to represent a superior, yet realistic, alternative to conventional Doppler processing for color flow mapping     

Clutter rejection filters in color flow imaging: a theoretical approach

A general class of linear clutter rejection filters is described, covering the commonly used filter types including FIR/IIR filters with linear initialization, as well as regression filters, where the clutter component is estimated by least square curve fitting. The filter can be described by a complex valued matrix, and a frequency response is defined. However, in contrast to a time invariant filter, the general linear filter may create frequency components which are not present in the input signal. This produces bias in the velocity and velocity spread estimates. It is shown that the clutter filter effect on the autocorrelation estimates can be described by a frequency domain transfer function, but unlike time invariant filters, the transfer function is different for each temporal lag of the autocorrelation function. Using a two dimensional (axial and temporal dimension) model of the received signal, the bias in velocity and velocity spread is quantified, both for the autocorrelation algorithm and the time shift cross-correlation estimator. Theoretical expressions, as well as numerical examples are given.     

Maximum likelihood blood velocity estimator incorporating properties of flow physics

The aspect of correlation among the blood velocities in time and space has not received much attention in previous blood velocity estimators. The theory of fluid mechanics predicts this property of the blood flow. Additionally, most estimators based on a cross-correlation analysis are limited on the maximum velocity detectable. This is due to the occurrence of multiple peaks in the cross-correlation function. In this study a new estimator (CMLE), which is based on correlation (C) properties inherited from fluid flow and maximum likelihood estimation (MLE), is derived and evaluated on a set of simulated and in vivo data from the carotid artery. The estimator is meant for two-dimensional (2-D) color flow imaging. The resulting mathematical relation for the estimator consists of two terms. The first term performs a cross-correlation analysis on the signal segment in the radio frequency (RF)-data under investigation. The flow physic properties are exploited in the second term, as the range of velocity values investigated in the cross-correlation analysis are compared to the velocity estimates in the temporal and spatial neighborhood of the signal segment under investigation. The new estimator has been compared to the cross-correlation (CC) estimator and the previously developed maximum likelihood estimator (MLE). The results show that the CMLE can handle a larger velocity search range and is capable of estimating even low velocity levels from tissue motion. The CC and the MLE produce incorrect velocity estimates due to the multiple peaks, when the velocity search range is increased above the maximum detectable velocity. The root-mean square error (RMS) on the velocity estimates for the simulated data is on the order of 7 cm/s (14%) for the CMLE, and it is comparable to the RMS for the CC and the MLE. When the velocity search range is set to twice the limit of the CC and the MLE, the number of incorrect velocity estimates are 0, 19.1, and 7.2% for the CMLE, CC, and MLE, respectively. The ability to handle a larger search range and estimating low velocity levels was confirmed on in vivo data.