A novel technique for the selective detection of ultrasound contrast agents, called pulse inversion Doppler, has been developed. In this technique, a conventional Doppler or color Doppler pulse sequence is modified by inverting every second transmit pulse. Either conventional or harmonic Doppler processing is then performed on the received echoes. In the resulting Doppler spectra, Doppler shifts from linear and nonlinear scattering are separated into two distinct regions that can be analyzed separately or combined to estimate the ratio of nonlinear to linear scattering from a region of tissue. The maximum Doppler shift that can be detected is 1/2 the normal Nyquist limit. This has the advantage over conventional harmonic Doppler that it can function over the entire bandwidth of the echo signal, thus achieving superior spatial resolution in the Doppler image. In vitro measurements comparing flowing agent and cellulose particles suggest that pulse inversion Doppler can provide 3 to 10 dB more agent to tissue contrast than harmonic imaging with similar pulses. Similar measurements suggest that broadband pulse inversion Doppler can provide up to 16 dB more contrast than broadband conventional Doppler. Nonlinear propagation effects limit the maximum contrast obtainable with both harmonic and pulse inversion Doppler techniques.

Pulse inversion Doppler: a new method for detecting nonlinear echoes from microbubble contrast agents

A novel technique for the selective detection of ultrasound contrast agents, called pulse inversion Doppler, has been developed. In this technique, a conventional Doppler pulse sequence is modified by inverting every second transmit pulse. Either conventional or harmonic Doppler processing is then performed on the received echoes. In the resulting Doppler spectra, Doppler shifts from linear and nonlinear scattering are separated into two distinct regions which can be analyzed separately or combined to estimate the ratio of nonlinear to linear scattering from a region of tissue. The maximum Doppler shift which can be detected is 1/2 the normal Nyquist limit. In vitro measurements comparing flowing agent and cellulose particles suggest that pulse inversion Doppler can provide 3 to 10 dB more agent to tissue contrast than harmonic imaging with similar pulses. Similar measurements suggest that broadband pulse inversion Doppler can provide up to 16 dB more contrast than broadband conventional Doppler.

Time delay estimation (TDE) lies at the heart of signal processing algorithms in a broad range of application areas, including communications, coherent imaging, speech processing, and acoustics. In medical ultrasound for example, TDE is used in blood flow estimation, tissue motion measurement, tissue elasticity estimation, phase aberration correction, and a number of other algorithms. Because of its central significance, TDE accuracy, precision, and computational cost are of critical importance. Furthermore, because TDE is typically performed on sampled signals - and delay estimates are usually desired over a continuous domain - time delay estimator performance should be considered in conjunction with associated interpolation. In this paper, we present a new time-delay estimator that directly determines continuous time-delay estimates from sampled data. The technique forms a spline-based, piece-wise continuous representation of the reference signal then solves for the minimum of the sum squared error between the reference and the delayed signals to determine their relative time delay. Computer simulation results clearly show that the proposed algorithm significantly outperforms other algorithms in terms of jitter and bias over a broad range of conditions. We also describe a modified version of the algorithm that includes companding with only a minor increase in computational cost

A spline-based algorithm for continuous time-delay estimation using sampled data

Achieving non-invasive, accurate and time-resolved imaging of vascular flow with spatiotemporal fluctuations is well acknowledged to be an ongoing challenge. In this article, we present a new ultrasound-based framework called vector projectile imaging (VPI) that can dynamically render complex flow patterns over an imaging view at millisecond time resolution. VPI is founded on three principles: (i) high-frame-rate broad-view data acquisition (based on steered plane wave firings); (ii) flow vector estimation derived from multi-angle Doppler analysis (coupled with data regularization and least-squares fitting); (iii) dynamic visualization of color-encoded vector projectiles (with flow speckles displayed as adjunct). Calibration results indicated that by using three transmit angles and three receive angles (-10°, 0°, +10° for both), VPI can consistently compute flow vectors in a multi-vessel phantom with three tubes positioned at different depths (1.5, 4, 6 cm), oriented at different angles (-10°, 0°, +10°) and of different sizes (dilated diameter: 2.2, 4.4 and 6.3 mm; steady flow rate: 2.5 mL/s). The practical merit of VPI was further illustrated through an anthropomorphic flow phantom investigation that considered both healthy and stenosed carotid bifurcation geometries. For the healthy bifurcation with 1.2-Hz carotid flow pulses, VPI was able to render multi-directional and spatiotemporally varying flow patterns (using a nominal frame rate of 416 fps or 2.4-ms time resolution). In the case of stenosed bifurcations (50% eccentric narrowing), VPI enabled dynamic visualization of flow jet and recirculation zones. These findings suggest that VPI holds promise as a new tool for complex flow analysis.

Vector Projectile Imaging: Time-Resolved Dynamic Visualization of Complex Flow Patterns

A practical method for identifying the propagation path of plant-wide disturbances

The cross-correlation method (CCM) for blood flow velocity measurement using Doppler ultrasound is based on time delay estimation of echoes from pulse-to-pulse. The sampling frequency of the received signal is usually kept as low as possible in order to reduce computational complexity, and the peak in the correlation function is found by interpolating the correlation function. The parabolic-fit interpolation method introduces a bias at low sampling rate to the ultrasound center frequency ratio. In this study, four different methods are suggested to improve the estimation accuracy: (1) Parabolic interpolation with bias-compensation, derived from a theoretical signal model. (2) Parabolic interpolation combined with linear filter interpolation of the correlation function. (3) Parabolic interpolation to the complex correlation function envelope. (4) Matched filter interpolation applied to the correlation function. The new interpolation methods are analyzed both by computer simulated signals and RF-signals recorded from a patient with time delay larger than 1/f/sub 0/, where f/sub 0/ is the center frequency. The simulation results show that these methods are more accurate than the parabolic-fit method. From the simulation, the worst estimation accuracy is about 1.25% of 1/f/sub 0/ for the parabolic-fit interpolation, and it is improved by the above methods to less than 0.5% of 1/f/sub 0/ when the sampling rate is 10 MHz, the center frequency is 2.5 MHz and the bandwidth is 1 MHz. This improvement also can be observed in the experimental data. Furthermore, the matched filter interpolation gives the best performance when signal-to-noise ratio (SNR) is low. This is verified both by simulation and experimentation.

/pdf/interpolation-methods-for-time-delay-estimation-using-cross-3sjwp8ath9.pdf

Interpolation methods for time-delay estimation using cross-correlation method for blood velocity measurement

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.

/pdf/an-extended-autocorrelation-method-for-estimation-of-blood-xr6zbkfe7p.pdf

Xiaoming Lai

Papers

Interpolation methods for time-delay estimation using cross-correlation method for blood velocity measurement

An extended autocorrelation method for estimation of blood velocity