Clutter Components Research Articles

Microvascular Flow Estimation by Contrast-Assisted Ultrasound B-Scan and Statistical Parametric Images

The microbubbles destruction/replenishment technique has been previously applied to estimating blood flow in the microcirculation. The rate of increase of the time-intensity curve (TIC) due to microbubbles flowing into the region of interest (ROI), as measured from B-mode images, closely reflects the flow velocity. In previous studies, we proposed a new approach called the time-Nakagami-parameter curve (TNC) obtained from Nakagami images to monitor microbubble replenishment for quantifying the microvascular flow velocity. This study aimed to further explore some effects that may affect the TNC to estimate the microflow, including microbubble concentration, ultrasound transmitting energy, attenuation, intrinsic noise, and tissue clutter. In order to well control each effect production, we applied a typical simulation method to investigate the TIC and TNC. The rates of increase of the TIC and TNC were expressed by the rate constants beta(I) and beta(N), respectively, of a monoexponential model. The results show that beta(N) quantifies the microvascular flow velocity similarly to the conventional beta(I) . Moreover, the measures of beta(I) and beta(N) are not influenced by microbubble concentration, transducer excitation energy, and attenuation effect. Although the effect of intrinsic signals contributed by noise and blood would influence the TNC behavior, the TNC method has a better tolerance of tissue clutter than the TIC does, allowing the presence of some clutter components in the ROI. The results suggest that the TNC method can be used as a complementary tool for the conventional TIC to reduce the wall filter requirements for blood flow measurement in the microcirculation.

SUBSPACE IMPULSIVE INTERFERENCE SUPPRESSION IN OTHR

This paper proposes a novel subspace projection algorithm for impulsive interference (IMI) suppression in echo samples received by an over-the-horizon radar (OTHR). We particularly highlight the model that the frequency spectrum of IMI component is a complex cosine signal such that IMI cosine can be filtered out by subspace projection. Compared with existing algorithms, a more simple clutter suppression algorithm is used to reject the most powerful clutter components. Furthermore, this algorithm will neither estimate nor need the exact temporal position of IMI, which avoids the impact resulted from the position estimation error. Another advantage is its little impact on true target signal and no impact on the clutter. Experimental results based on data from real high frequency surface wave (HFSW) OTHR systems are also shown to verify the proposed algorithm.

Adaptive clutter filtering based on sparse component analysis in ultrasound color flow imaging

An adaptive method based on the sparse component analysis is proposed for stronger clutter filtering in ultrasound color flow imaging (CFI). In the present method, the focal underdetermined system solver (FOCUSS) algorithm is employed, and the iteration of the algorithm is based on weighted norm minimization of the dependent variable with the weights being a function of the preceding iterative solutions. By finding the localized energy solution vector representing strong clutter components, the FOCUSS algorithm first extracts the clutter from the original signal. However, the different initialization of the basis function matrix has an impact on the filtering performance of FOCUSS algorithms. Thus, 2 FOCUSS clutter- filtering methods, the original and the modified, are obtained by initializing the basis function matrix using a predetermined set of monotone sinusoids and using the discrete Karhunen-Loeve transform (DKLT) and spatial averaging, respectively. Validation of 2 FOCUSS filtering methods has been performed through experimental tests, in which they were compared with several conventional clutter filters using simplistic simulated and gathered clinical data. The results demonstrate that 2 FOCUSS filtering methods can follow signal varying adaptively and perform clutter filtering effectively. Moreover, the modified method may obtain the further improved filtering performance and retain more blood flow information in regions close to vessel walls.

A clutter removal method for the Doppler ultrasound signal based on a nonlinear diffusion equation

Strong clutter components produced by stationary and slow-moving tissue structures render the lower frequency part of the spectrogram useless and degrade the accuracy of clinical ultrasound indices. An adaptive method based on the nonlinear forward-and-backward diffusion equation (FAB-DE) is proposed to remove strong clutter components from the contaminated Doppler signal. The clutter signal is extracted first by the FAB-DE accurately, in which the nonlinear diffusion coefficient function of the FAB-DE locally adjusts according to signal features and the diffusion adaptively switches between forward and backward mode. The present method has been validated by simulated and realistic pulse wave Doppler signals, and compared with the conventional high pass filter and the matching pursuit method. The simulation results, including spectrogram, mean velocity error, standard deviation of mean velocity and signal-to-clutter ratio of a decontaminated signal, demonstrate that the present FAB-DE method can remove clutter sufficiently and retain more low blood components simultaneously as compared with the other two methods. Results of the realistic Doppler blood signal, including spectrogram and low-frequency part of the spectrum, support the conclusion drawn from simulation cases.

Clutter rejection filters for optical Doppler tomography

The phase-resolved (PR) method is widely used in optical Doppler tomography (ODT) to estimate flow velocity from sequential axial line (A-line) signals. However, the A-line signal contains clutter components induced by stationary or relative slow moving clutter scatterers such as the blood vessel wall or the overall sample with motion artifacts. The clutter component affects the accuracy in quantifying Doppler flow. In this paper, we present a delay line filter (DLF) to reject the clutter effect and enables moving-scatterer-sensitive ODT (MSS-ODT) imaging of flow. The frequency response of DLFs of different orders is theoretically analyzed and we find that a first-order phase-shifted DLF is effective for clutter rejection and for improving the sensitivity to moving scatterers such as moving blood cells. The proposed MSS-ODT method has been experimentally applied to Doppler flow imaging in a capillary flow phantom and a mouse ear in vivo. The ODT data were acquired using a real-time spectral-domain optical coherence tomography (SD-OCT) system with an A-line acquisition rate of 12.3k/s. Doppler flow images obtained with MSS-ODT and the conventional PR-ODT techniques are compared and MSS-ODT is found to be more sensitive to Doppler flow and more accurate in determining vessel size. Small blood vessels that might be masked by clutter signals in PR-OCT are successfully recovered by MSS-ODT.

Ground-Penetrating Radar Data Preprocessing

An algorithm for dynamic selection of clutter components in a signal of a videopulse ground-penetrating radar (GPR) is proposed. Clutter-resistant estimates of radio contracts are made. The robustness of these estimates has been achieved by optimal data weighting. An algorithm of suppressing anomalous bursts in a signal is proposed. The ways to subsequently elaborate the techniques for preprocessing these types of signals are discussed.

Adaptive clutter filtering via blind source separation for two-dimensional ultrasonic blood velocity measurement.

A method for adaptive clutter rejection via blind source separation (BSS) using principal and independent component analyses is presented in application to blood velocity measurement in the carotid artery. In particular, the filtering method's efficacy for eliminating clutter and preserving lateral blood flow signal components is presented. The performance of IIR filters is compromised by shorth data ensembles (10 to 20 temporal samples) as implemented for color-flow and high frame-rate imaging due to initialization requirements. Further, the ultrasonic imaging system's transfer function maps axial wall and lateral blood motion to overlapping spectra. As such, frequency domain-based approaches to wall filtering are ineffective for distinguishing wall from blood motion signals. Rather than operating in the frequency domain. BSS performs clutter rejection by decomposing the input data ensemble into N constitutive source signals in time, where N is the ensemble length. Source signal energy coupled with respective signal depth and time course profiles reveal which source signals correspond to blood, noise and clutter components. Clutter components may then be removed without disruption of lateral blood flow information needed for two-dimensional blood velocity measurement. A simplistic data simulation is employed to offer an intuitive understanding of BSS methods for signal separation. The adaptive BSS filter is further demonstrated using a Field II simulation of blood flow through the carotid artery including tissue motion. BSS clutter filter performance is compared to the performance of FIR, IIR and polynomial regression clutter filters. Finally, the filter is employed for clinical application using a Siemens Elegra scanner, carotid artery data with lateral blood flow collected from healthy volunteers, and Speckle Tracking; velocity magnitude and angle profiles are shown. Once again, the BSS clutter filter is contrasted to FIR, IIR and polynomial regression clutter filters using clinical examples. Velocities computed with Speckle Tracking after BSS wall filtering are highest in the center of the artery and diminish to low velocities near the vessel walls, with velocity magnitudes consistent with physiological expectations. These results demonstrate that the BSS adaptive filter sufficiently suppresses wall motion signal for clinical lateral blood velocity measurement using data ensembles suitable for color-flow and high frame-rate imaging.

Simulation model of correlated K-distributed clutter

It is shown that each quadrature component of K-distributed clutter with shape parameter V/spl ges/1/2 can be modelled, exactly or approximately, by a weighted sum of products of two independent Gaussian variables. The normalised autocorrelation function of such simulated clutter components can assume values from the entire range(-1,1).

High resolution radar clutter statistics

The generalized compound probability density function (GC-pdf) is presented for modeling high resolution radar clutter. In particular, the model is used to describe deviation of the speckle component from the Rayleigh to Weibull or other pdfs with longer tails. The GC-pdf is formed using the generalized gamma (G/spl Gamma/) pdf to describe both the speckle and the modulation component of the radar clutter. The proposed model is analyzed and thermal noise is incorporated into it. The validation of the GC-pdf with real data is carried out employing the statistical moments as well as goodness-of-fit tests. A large variety of experimental data is used for this purpose. The GC-pdf outperforms the K-pdf in modeling high resolution radar clutter and reveals its structural characteristics.

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.

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.

Reduction of the clutter component in Doppler ultrasound signals based on singular value decomposition: a simulation study.

In pulsed Doppler ultrasound systems, the ultrasound radiofrequency (RF) signals received can be employed to estimate noninvasively the time-dependent blood velocity distribution within and artery. The RF signals are composed of signals originating from clutter (e.g., vessel walls) and scatterers (e.g., red blood cells). The clutter, which is induced by stationary or slowly-moving structure interfaces, must be suppressed to get reliable estimates of the mean blood flow velocities. In conventional pulsed Doppler systems, this is achieved with a static temporal high-pass filter. The static cut-off frequency and the roll-off of these filters cause the culture not always to be optimally suppressed. This paper introduces a clutter removal filter that is based on Singular Value Decomposition (SVD). Unlike conventional high-pass filters, which take into account only the information of the temporal direction, the SVD filter makes use of the information of the temporal and spatial directions. The advantage of this approach is that it does not matter where the clutter is located in the RF signal. The performance of the SVD filter is examined with computer-generated Doppler RF signals. The results are compared with those of standard linear regression (SLR) filter. The performance of the SVD filter is good, especially if a large temporal window (i.e., approximately 100 RF signals) is applied, which improves the performance for low blood flow velocities, A major disadvantage of the SVD filter is its computational complexity, which increases considerably for larger temporal windows.

A doppler ultrasound clutter phantom

We describe two variations of a phantom designed to evaluate the wall filters implemented on colour and spectral Doppler instruments. Both variations use an acoustic beam splitter to place the same Doppler sample volume within a motor-driven clutter belt and a flow source, which is either a second belt (dual-belt phantom) or a vascular phantom (belt/vascular phantom). We used the dual-belt phantom to evaluate the effects of the clutter belt velocity, flow belt velocity and clutter-to-flow power ratio on the reported colour Doppler shifts. The results show that the choice of wall filter, as well as the amplitudes and velocities of the clutter and flow components, affect the measured Doppler shifts. Results obtained with the belt/vascular phantom show that colour Doppler shifts due to the moving fluid depend strongly on the clutter velocity and choice of wall filter. However, only a small dependence on Doppler signal strength was observed.

Suppression of terrain-scattered jamming in pulse compression radar

This letter presents research results on a new method for the suppression of terrain-scattered clutter due to jamming of the radar footprint. The method applies temporal adaptive filtering to the received radar signal that removes the correlated clutter component. This approach relies on the transmitted radar signal having coded phases, such as a discretized chirp or polyphase waveform. Because of the prior knowledge of coded phase of the transmitted waveform, it is not necessary to have an auxiliary record of the jamming signal to achieve clutter suppression. >

Ultrasonic Doppler imaging apparatus

First Page

First observation of the upper stratospheric vertical wind velocities using the Jicamarca VHF radar

The Jicamarca VHF radar (50 MHz) has detected atmospheric echoes in the so‐called ”gap region” from 30 to 60 km heights. These echoes are, for the first time, discriminated from clutter echoes, using both co‐polarized (co‐pol) and cross‐polarized (x‐pol) arrays to monitor the clutter component which may enter the antenna sidelobes. The atmospheric scatterings in this region are shown to be composed of refractivity layers with thickness as of 1–2 km as in other middle atmospheric height ranges, suggesting that these scatterings are caused by thin turbulent layers. The height profile of inferred vertical wind velocities indicates a wavy structure. The wave amplitude, as a whole, increases with height, suggesting the activity of upward‐propagating gravity waves.

Spectral Analysis and Subtraction of Noise in Radar Signals

A new method of maximum entropy spectral estimation called the revised maximum entropy method (MEM) is formulated and is applied to the spectral analysis of the echo signals from atmospheric turbulence observed by an incoherent scatter radar. The revised MEM is shown free from many demerits of the other methods for spectral analysis. Further it makes it possible to subtract the white noise usually contained in the data during the processing. Some examples of spectral estimation are shown for the actual radar signals and the simulated data. Another application of the revised MEM is the subtraction of the clutter component which is difficult to do by linear filtering. The method is successfully applied to several data abounding with the clutter to obtain the spectra of the echo signals with less clutter distortion.

Class of optimum m.t.i. filters for clutter rejection

The problem of optimum design of an m.t.i. system for clutter rejection is considered in this paper. The procedure involves minimisation of the output clutter power subject to the constraint that the average output-signal power over the expected target Doppler range is to be kept constant. Another constraint in the minimisation problem is incorporated, according to which the transfer function of the system has a null at the dominant clutter Doppler frequency fm, which may often be zero. In this way, the distributed component of clutter is minimised at the filter output while the clutter component at a fixed mean relative velocity is completedly suppressed. With the two constraints specified above, the problem is mathematically formulated as a modified eigenvalue problem. Comprehensive results for the performance of the resulting filters are presented.

Estimating the correlation coefficient of highly correlated clutter

A maximum-likelihood estimator for the pulse-to-pulse correlation coefficient r of Rayleigh-distributed clutter components is considered. For r greater than 0.9, an approximate computationally feasible estimator is derived. Results of Monte Carlo simulation indicate that the approximate estimator is only slightly inferior to the maximum-likelihood estimator.

A Quantitative Analysis of Sea Clutter Decorrelation with Frequency Agility

A brief statement of the sea clutter problem in surface-search radar operation illustrates the need for some form of signal-to-clutter enhancement. Post-detection integration used in the simpler radars is limited by the pulse-to-pulse correlation of the clutter. Analysis of the effect of changing frequency from pulse to pulse leads to an expression for the correlation between pulses in the sequence. Knowing this correlation, the reduction in the fluctuating clutter component produced by integration can be determined. This is described by an equivalent number of independent pulses, Nc. For the particular case of sinusoidal modulation of the transmitted frequency, N6 is computed. The critical dependecne of Nc upon the modulating frequency fm is illustrated by spectrum photographs. Choice of an optimum fm is discussed. The results of computations of N4 for optimum fm are presented as a family of normalized curves. These data permit the tradeoff of the radar parameters against their quantitative effect on radar performance.