共查询到20条相似文献,搜索用时 15 毫秒
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Løvstakken L Bjaerum S Kristoffersen K Haaverstad R Torp H 《IEEE transactions on ultrasonics, ferroelectrics, and frequency control》2006,53(9):1597-1608
We propose a new algorithm for real-time, adaptive-clutter-rejection filtering in ultrasound color flow imaging (CFI) and related techniques. The algorithm is based on regression filtering using eigenvectors of the signal correlation matrix as a basis for representing clutter, a method that previously has been considered too computationally demanding for real-time processing in general CFI applications. The data acquisition and processing scheme introduced allows for a more localized sampling of the clutter statistics and, therefore, an improved clutter attenuation for lower filter orders. By using the iterative power method technique, the dominant eigenvalues and corresponding eigenvectors of the correlation matrix can be estimated efficiently, rendering real-time operation feasible on desktop computers. A new adaptive filter order algorithm is proposed that successfully estimates the proper dimension of the clutter basis, previously one of the major drawbacks of this clutter-rejection technique. The filter algorithm performance and computational demands has been compared to that of conventional clutter filters. Examples have been included which confirms that, by adapting the clutter-rejection filter to estimates of the clutter-signal statistics, improved attenuation of the clutter signal can be achieved in normal as well as more excessive cases of tissue movement and acceleration. 相似文献
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Løvstakken L Bjaerum S Torp H 《IEEE transactions on ultrasonics, ferroelectrics, and frequency control》2007,54(3):539-549
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. 相似文献
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You W. Wang Y. 《IEEE transactions on ultrasonics, ferroelectrics, and frequency control》2009,56(10):2217-2231
In the conventional eigenfilter used to reject clutter components of ultrasound color flow imaging, input samples are required to be statistically stationary. However, clutter movements may vary over the depth of the imaged area, which makes the eigenfilter less efficient. In the current study, a novel clutter rejection method is proposed based on the recursive eigendecomposition algorithm. In this method, the current eigenvector matrix of the ultrasound echo correlation matrix, which will be used to construct the clutter subspace, is determined by previous eigenvector matrices and the current input. After the estimated clutter signal is obtained by projecting the original input into the clutter space, each filtered output is eventually obtained by subtracting the estimated clutter signal from the original input. This procedure is iterated for each sample volume along the depth. During the updating process, a forgetting factor is introduced to determine proper weights for different inputs. Simulated data in 3 situations and in vivo data collected from human carotid arteries are used to compare the proposed method with other popular clutter filters. Results show that the proposed method can achieve the most accurate velocity profiles in all simulation situations and introduces the fewest velocity artifacts in the tissue region in the in vivo experiment. 相似文献
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Bjaerum S Torp H Kristoffersen K 《IEEE transactions on ultrasonics, ferroelectrics, and frequency control》2002,49(6):693-704
The quality of ultrasound color flow images is highly dependent on sufficient attenuation of the clutter signals originating from stationary and slowly moving tissue. Without sufficient clutter rejection, the detection of low velocity blood flow will be poor, and the velocity estimates will have a large bias. In some situations, e.g., when imaging the coronary arteries or when the operator moves the probe in search for small vessels, there is considerable movement of tissue. It has been suggested that clutter rejection can be improved by mixing down the signal with an estimate of the mean frequency prior to high pass filtering. In this paper, we compare this algorithm with several other adaptive clutter filtering algorithms using both experimental data and simulations. We found that realistic accelerations of the tissue have a large effect on the clutter rejection. The best results were obtained by mixing down the signal with non-constant phase increments estimated from the signal. This adapted the filter to a possibly accelerated tissue motion and produced a significant improvement in clutter rejection 相似文献
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In the heavy clutter environment, the information capacity is large, the relationships among information are complicated, and track initiation often has a high false alarm rate or missing alarm rate. Obviously, it is a difficult task to get a high-quality track initiation in the limited measurement cycles. This paper studies the multi-target track initiation in heavy clutter. At first, a relaxed logic-based clutter filter algorithm is presented. In the algorithm, the raw measurement is filtered by using the relaxed logic method. We not only design a kind of incremental and adaptive filtering gate, but also add the angle extrapolation based on polynomial extrapolation. The algorithm eliminates most of the clutter and obtains the environment with high detection rate and less clutter. Then, we propose a fuzzy sequential Hough transform-based track initiation algorithm. The algorithm establishes a new meshing rule according to system noise to balance the relationship between the grid granularity and the track initiation quality. And a flexible superposition matrix based on fuzzy clustering is constructed, which avoids the transformation error caused by 0–1 voting method in traditional Hough transform. In addition, the algorithm allows the superposition matrixes of nonadjacent cycles to be associated to overcome the shortcoming that the track can’t be initiated in time when the measurements appear in an intermittent way. And a slope verification method is introduced to detect formation-intensive serial tracks. Last, the sliding window method is employed to feedback the track initiation results timely and confirm the track. Simulation results verify that the proposed algorithms can initiate the tracks accurately in heavy clutter. 相似文献
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Yu AC Cobbold RS 《IEEE transactions on ultrasonics, ferroelectrics, and frequency control》2008,55(3):573-587
Parametric spectral estimators can potentially be used to obtain flow estimates directly from raw slow-time ensembles whose clutter has not been suppressed. We present a new eigen-based parametric flow estimation method called the matrix pencil, whose principles are based on a matrix form under the same name. The presented method models the slow-time signal as a sum of dominant complex sinusoids in the slow-time ensemble, and it computes the principal Doppler frequencies by using a generalized eigen-value problem-formulation and matrix rank reduction principles. Both fixed rank (rank-one, rank-two) and adaptive-rank matrix pencil flow estimators are proposed, and their potential applicability to color flow signal processing is discussed. For the adaptive-rank estimator, the nominal rank was defined as the minimum eigen-structure rank that yields principal frequency estimates with a spread greater than a prescribed bandwidth. In our initial performance evaluation, the fixed-rank matrix pencil estimators were applied to raw color flow data (transmit frequency: 5 MHz; pulse repetition period: 0.175 ms; ensemble size: 14) acquired from a steady flow phantom (70 cm/s at centerline) that was surrounded by rigid-tissue-mimicking material. These fixed-rank estimators produced velocity maps that are well correlated with the theoretical flow profile (correlation coefficient: 0.964 to 0.975). To facilitate further evaluation, the matrix pencil estimators were applied to synthetic slow-time data (transmit frequency: 5 MHz; pulse repetition period: 1.0 ms; ensemble size: 10) modeling flow scenarios without and with tissue motion (up to 1 cm/s). The bias and root-mean-squared error of the estimators were computed as a function of blood-signal-to-noise ratio and blood velocity. The matrix pencil flow estimators showed that they are comparatively less biased than most of the existing frequency-based flow estimators like the lagone autocorrelator. 相似文献
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The signal processing problem has become increasingly complex and demand high acquisition system, this paper proposes a new method to reconstruct the structure phased array structural health monitoring signal. The method is derived from the compressive sensing theory and the signal is reconstructed by using the basis pursuit algorithm to process the ultrasonic phased array signals. According to the principles of the compressive sensing and signal processing method, non-sparse ultrasonic signals are converted to sparse signals by using sparse transform. The sparse coefficients are obtained by sparse decomposition of the original signal, and then the observation matrix is constructed according to the corresponding sparse coefficients. Finally, the original signal is reconstructed by using basis pursuit algorithm, and error analysis is carried on. Experimental research analysis shows that the signal reconstruction method can reduce the signal complexity and required the space efficiently. 相似文献
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《Radar, Sonar & Navigation, IET》2007,1(1):38-49
A de-emphasis weighting approach is used to suppress the effect of outliers in background samples during the formation of a sample covariance matrix. The approach is relevant to a broad range of adaptive filtering techniques. Results from processing simulated and real coherent radar data using de-emphasis weighting are compared with results using no outlier suppression and censored sample matrix inversion pruning methods. De-emphasis techniques are shown to produce the most robust detection performance when outliers are present and are also shown to have minimal performance impact when clutter is homogeneous, that is no outliers present 相似文献
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基于局部保持投影发展出的一系列特征提取算法,在应用于人脸识别等高维小样本问题时,均需先采用PCA算法对高维样本降维后才能应用,故此以无监督鉴别分析算法为理论基础,提出了一种直接无监督正交局部保持算法。该算法利用拉普拉斯矩阵的性质进行相应的矩阵分解,可直接从高维样本的原始空间中提取投影矩阵,因而无需先采用PCA降维处理,且解决了无监督鉴别分析算法的小样本问题。为了进一步提高算法的识别性能,给出了基于QR分解的正交投影矩阵的求解方法。人脸库和掌纹库上的实验结果表明了所提算法的有效性。 相似文献
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Clutter filter design for ultrasound color flow imaging 总被引:7,自引:0,他引:7
Bjaerum S Torp H Kristoffersen K 《IEEE transactions on ultrasonics, ferroelectrics, and frequency control》2002,49(2):204-216
For ultrasound color flow images with high quality, it is important to suppress the clutter signals originating from stationary and slowly moving tissue sufficiently. Without sufficient clutter rejection, low velocity blood flow cannot be measured, and estimates of higher velocities will have a large bias. The small number of samples available (8 to 16) makes clutter filtering in color flow imaging a challenging problem. In this paper, we review and analyze three classes of filters: finite impulse response (FIR), infinite impulse response (IIR), and regression filters. The quality of the filters was assessed based on the frequency response, as well as on the bias and variance of a mean blood velocity estimator using an autocorrelation technique. For FIR filters, the frequency response was improved by allowing a non-linear phase response. By estimating the mean blood flow velocity from two vectors filtered in the forward and backward direction, respectively, the standard deviation was significantly lower with a minimum phase filter than with a linear phase filter. For IIR filters applied to short signals, the transient part of the output signal is important. We analyzed zero, step, and projection initialization, and found that projection initialization gave the best filters. For regression filters, polynomial basis functions provide effective clutter suppression. The best filters from each of the three classes gave comparable bias and variance of the mean blood velocity estimates. However, polynomial regression filters and projection-initialized IIR filters had a slightly better frequency response than could be obtained with FIR filters 相似文献
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It is well known that in the airborne radar, the location of the ground clutter spectrum in the angle- Doppler space is dependent mainly on the platform velocity and radar parameters. The authors propose a two-dimensional pulse-to-pulse canceller (TDPC) that can make full use of such prior information. The more detailed formulations of the ground clutter model and the signal model are given in a matrix?vector form. The least-squares-typical cost function associated with the filter coefficient matrix of the TDPC is established on the basis of the ground clutter model and the signal model. Like the classical displaced phase centre antenna (DPCA) processing, the proposed TDPC is also a spatial-temporal suppressor of ground clutter and can decrease the ground clutter signals, even though the DPCA condition is not satisfied. The proposed TDPC can also be used as an efficient pre-filtering tool before the conventional moving target indication (MTI) processing and the classical adaptive processing. Moreover, if only the TDPC plus the conventional MTI is used, it takes less computational time than the adaptive canceller. Experimental results show that the proposed TDPC has the satisfactory ground clutter suppression capability by using both simulated data and measured data. 相似文献
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Complex process monitoring using modified partial least squares method of independent component regression 总被引:1,自引:0,他引:1
In this paper, first, some disadvantages of original partial least squares method of independent component analysis (ICA-PLS) are analyzed. Then ICA-PLS is modified for regression purpose.Disadvantages of the original ICA-PLS algorithm are as follows: 1) the regression coefficient matrix and residual matrix cannot been given so that the computation time may increase with the number of samples; and 2) ICA-PLS lacks the ability to give better monitoring performance when the correlation structure of measured variables is nonlinear, which is often the case for industrial processes.To solve the above problems, we modified the original algorithm in following aspects: 1) the regression coefficient matrix and residual matrix in ICA-PLS are given so that the computation time is decreased; and 2) to solve the nonlinear problem, ICA-PLS and kernel trick is first combined for nonlinear regression purpose, which is called iterative ICA-KPLS in this paper. The iterative calculation of ICA-KPLS will be time consuming when the sample number becomes larger. Hence, the regression coefficient matrix and residual matrix in ICA-KPLS are given to avoid the expensive computation time when the number of samples is huge.The proposed methods are applied to the quality prediction in fermentation process and Tennessee Eastman process. Applications indicate that the proposed approach effectively captures the relations in the process variables and use of ICA-KPLS instead of ICA-PLS improves the predictive ability. The expensive computation time is avoided by using the coefficient matrix and residual matrix. 相似文献
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A new high resolution color flow system using an eigendecomposition-based adaptive filter for clutter rejection 总被引:1,自引:0,他引:1
Kruse DE Ferrara KW 《IEEE transactions on ultrasonics, ferroelectrics, and frequency control》2002,49(10):1384-1399
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. 相似文献
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Kruse DE Ferrara KW 《IEEE transactions on ultrasonics, ferroelectrics, and frequency control》2002,49(12):1739-1754
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. 相似文献
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本文将分形Hǒlder指数和信号分离相结合,利用独立成分分析技术(ICA,Independent Component Analysis),实现了海杂波SAR图的散斑抑制和点目标检测。首先,计算点态Hǒlder指数图,并提出二值模糊方法对其处理;接着使用ICA技术得到该图的基图像和独立成分;提出空间分离法,对独立成分进行分离,同时对基图进行对应分类,获得非噪声和噪声两个空间。最后在非噪声空间上重构图像。实验部分,将该算法与传统算法进行对比,证实了该算法的有效性和优越性。 相似文献