Vibrating interventional device detection using real-time 3-D color Doppler

Ultrasound image guidance of interventional devices during minimally invasive surgery provides the clinician with improved soft tissue contrast while reducing ionizing radiation exposure. One problem with ultrasound image guidance is poor visualization of the device tip during the clinical procedure. We have described previously guidance of several interventional devices using a real-time 3-D (RT3-D) ultrasound system with 3-D color Doppler combined with the ColorMark technology. We then developed an analytical model for a vibrating needle to maximize the tip vibrations and improve the reliability and sensitivity of our technique. In this paper, we use the analytical model and improved radiofrequency (RF) and color Doppler filters to detect two different vibrating devices in water tank experiments as well as in an in vivo canine experiment. We performed water tank experiments with four different 3- D transducers: a 5 MHz transesophageal (TEE) probe, a 5 MHz transthoracic (TTE) probe, a 5 MHz intracardiac catheter (ICE) transducer, and a 2.5 MHz commercial TTE probe. Each transducer was used to scan an aortic graft suspended in the water tank. An atrial septal puncture needle and an endomyocardial biopsy forceps, each vibrating at 1.3 kHz, were inserted into the vascular graft and were tracked using 3-D color Doppler. Improved RF and wall filters increased the detected color Doppler sensitivity by 14 dB. In three simultaneous planes from the in vivo 3-D scan, we identified both the septal puncture needle and the biopsy forceps within the right atrium using the 2.5 MHz probe. A new display filter was used to suppress the unwanted flash artifact associated with physiological motion.     

基于MATLAB的PDV系统数据处理算法与实现

光子多普勒测振(Photonic Doppler Vibrometer,PDV)系统具有测量精度高、空间分辨力高、动态响应快等优点,适用于高温、高压、高速等特殊环境,应用范围广泛。数据处理是PDV系统的重要技术部分,旨在从含有大量噪声的测量数据中获得被测运动体的速度信息。本文在条纹法的基础上,针对原始信号的去噪、奇异点等问题,分别采用移动均值滤波以及小波变换法进行处理,最终得到被测物体的振动信息。利用激振台与经校准的激光测振仪进行振动测试对比实验,验证了该数据处理方法的可靠性和普适性。     

Time-scale removal of "wall thump" in Doppler ultrasound signals: a simulation study

A novel approach for blood and wall signal separation in Doppler ultrasound is proposed in the wavelet time-scale domain. The Doppler signals of different clutter-to-blood ratios from a femoral artery were simulated and used in the experiments. Compared with the conventional high-pass filtering and the signal separation in the spectrogram, the new method delivers improved performance for "wall thump" removal with minimal loss of low-flow signal.     

包装过程称量信号处理方法研究

目的 为提高包装过程定量称量精度,结合卡尔曼滤波算法和模糊控制原理设计一种称量信号处理方法。方法 定量称量控制系统一般由触摸屏、控制器、称量传感器、变频器等电气设备组成。以传感器信号处理为主要研究对象,提出一种改进卡尔曼滤波算法。采用卡尔曼滤波器实现称量信号中随机噪声的处理。利用模糊控制器来实时监测卡尔曼滤波每次更新后实际方差和理论方差的差值。最后,进行实验研究。结果 实验结果表明,改进卡尔曼滤波的实际性能比较理想,滤波处理前,称量误差最大可以达到2.5%;经滤波处理后,最大称量误差只有0.26%。结论 所述信号处理方法可以有效地降低称量信号噪声,提高称量精度。     

A sigma-delta-based sparse synthetic aperture beamformer for real-time 3-D ultrasound

Sigma-delta (ΣΔ) modulation allows delay resolution in ultrasound beamformers to be achieved by simple clock cycle delays applied to the undecimated bitstream, greatly reducing the complexity of the signal processing and the number of bits in the datapath. The simplifications offered by this technique have the potential for low power and portable operation in advanced systems such as 3-D and color Doppler imagers. In this paper, an architecture for a portable, real-time, 3-D sparse synthetic aperture ultrasound beamformer based on ΣΔ modulation is presented, and its simulated performance is analyzed. Specifically, with a 65-element linear phased array and three transmit events, this architecture is shown to achieve a 1.1° beamwidth, a -54-dB secondary lobe level, and a theoretical frame rate of 1700 frames/s at λ/64 delay resolution using a second-order low pass ΣΔ modulator. Finally, a technique for modifying the proposed multi-beam architecture to allow improved analog-to-digital (A/D) resolution by premodulating the input signal for bandpass ΣΔ modulation is also presented     

彩超诊断胰腺炎的临床价值分析

目的:对彩超诊断胰腺炎的临床价值进行分析。方法:选取我院2012年1月-2013年11月收治的胰腺炎患者53例,回顾分析其应用彩超诊断的临床资料。结果:经过彩超的明确诊断,53例患者中,有急性胰腺炎的患者41例,慢性胰腺炎的患者12例。其中,急性水肿型胰腺炎患者33例,急性出血坏死型胰腺炎患者8例。结论:胰腺炎病症应用彩超诊断更为简便迅速、安全可靠,检出率相对较高,值得临床中广泛应用。     

Real-time adaptive clutter rejection filtering in color flow imaging using power method iterations

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.     

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.     

Techniques for perfusion imaging with microbubble contrast agents

The acoustic properties of ultrasound contrast agents vary widely with agent composition and insonation conditions. For contrast imaging, methods are required to match RF and Doppler processing to each combination of transmission parameters and agent and tissue properties. We propose a method that uses the measured or modeled echoes from agent and tissue to specify directly the characteristics of RF and Doppler filters for contrast imaging. The proposed method is sufficiently general to cover most common imaging techniques including harmonic greyscale, Doppler, and pulse inversion imaging. Using this method, sample filters were designed to detect myocardial perfusion with the contrast agent Optison^TM (Mallinckrodt Medical, St. Louis, MO) under selected imaging conditions. Simplified power Doppler filtering, using a weighted sum of the Doppler samples, matched the performance of more complicated matrix filters. By coordinating the selection of RF and Doppler filters rather than designing these filters sequentially, agent-to-tissue contrast was increased by up to 3.9 dB. Under some conditions, fundamental RF filtering outperformed harmonic filtering for intermittent Doppler imaging     

Ultrawideband coherent noise lidar range-Doppler imaging and signal processing by use of spatial-spectral holography in inhomogeneously broadened absorbers

We introduce a new approach to coherent lidar range-Doppler sensing by utilizing random-noise illuminating waveforms and a quantum-optical, parallel sensor based on spatial-spectral holography (SSH) in a cryogenically cooled inhomogeneously broadened absorber (IBA) crystal. Interference between a reference signal and the lidar return in the spectrally selective absorption band of the IBA is used to sense the lidar returns and perform the front-end range-correlation signal processing. Modulating the reference by an array of Doppler compensating frequency shifts enables multichannel Doppler filtering. This SSH sensor performs much of the postdetection signal processing, increases the lidar system sensitivity through range-correlation gain before detection, and is capable of not only Doppler processing but also parallel multibeam reception using the high-spatial resolution of the IBA crystals. This approach permits the use of ultrawideband, high-power, random-noise, cw lasers as ranging waveforms in lidar systems instead of highly stabilized, injection-seeded, and amplified pulsed or modulated laser sources as required by most conventional coherent lidar systems. The capabilities of the IBA media for many tens of gigahertz bandwidth and resolution in the 30-300 kHz regime, while using either a pseudo-noise-coded waveform or just a high-power, noisy laser with a broad linewidth (e.g., a truly random noise lidar) may enable a new generation of improved lidar sensors and processors. Preliminary experimental demonstrations of lidar ranging and simulation on range-Doppler processing are presented.     

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 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.     

Design and implementation of a smartphone-based portable ultrasound pulsed-wave Doppler device for blood flow measurement

Blood flow measurement using Doppler ultrasound has become a useful tool for diagnosing cardiovascular diseases and as a physiological monitor. Recently, pocket-sized ultrasound scanners have been introduced for portable diagnosis. The present paper reports the implementation of a portable ultrasound pulsed-wave (PW) Doppler flowmeter using a smartphone. A 10-MHz ultrasonic surface transducer was designed for the dynamic monitoring of blood flow velocity. The directional baseband Doppler shift signals were obtained using a portable analog circuit system. After hardware processing, the Doppler signals were fed directly to a smartphone for Doppler spectrogram analysis and display in real time. To the best of our knowledge, this is the first report of the use of this system for medical ultrasound Doppler signal processing. A Couette flow phantom, consisting of two parallel disks with a 2-mm gap, was used to evaluate and calibrate the device. Doppler spectrograms of porcine blood flow were measured using this stand-alone portable device under the pulsatile condition. Subsequently, in vivo portable system verification was performed by measuring the arterial blood flow of a rat and comparing the results with the measurement from a commercial ultrasound duplex scanner. All of the results demonstrated the potential for using a smartphone as a novel embedded system for portable medical ultrasound applications.     

基于FPGA的激光外差干涉仪反正切解调技术

针对高频声学应用中多普勒信号软件解调的局限,提出了一种基于FPGA的数字硬件信号解调方案.基于AD9467设计了高速ADC采集系统,以实现原始多普勒信号的奈奎斯特采样或带通采样;基于Xilinx Zynq-7000片上芯片系统设计数字信号处理系统,实现了 DDS合成参考信号与多普勒信号混频、低通滤波产生I&Q基带信号对...     

工频干扰振动信号的建模与分离处理

针对钻井泵振动测试过程中遇到的工频干扰，采用信号的基元分段方法进行测试信号的合理分段处理，结合最优频率匹配法实现分段后干扰信号的建模分析。在此基础上提出振动信号的匹配滤波法，实现干扰信号与钻井泵振动信号的匹配滤波分离。实践表明，最优频率匹配法可以实现各种信号的数学建模，是一种通用性的信号建模处理有效的新方法，而且建立在该方法基础上的匹配滤波法也可以较为完整、合理地分离各种时、频域混叠信号，是一种适应性强的信号滤波处理新方法。     

A new pulsed wave Doppler ultrasound system to measure bloodvelocities beyond the Nyquist limit

Conventional pulsed wave (PW) Doppler ultrasound systems measure blood velocities unambiguously as long as the velocities are less than the Nyquist velocity. Here, a new PW Doppler ultrasound system is described, which can measure velocities up to 4.5 times higher than the Nyquist velocity. The new PW system presented here utilizes two ultrasound carrier frequencies, such that an appropriate processing of the Doppler frequencies results in an extended mean-velocity range. With this extended mean-velocity information, the complex Doppler signal is interpolated to reconstruct aliased Doppler spectra. The interpolation algorithm has been tested by computer simulations demonstrating the capabilities and limits. The integration into a commercial Doppler scanner allowed the evaluation of the new PW system in real time. In vitro and in vivo tests demonstrate the effective reconstruction of highly aliased Doppler spectra     

Isomorphism between pulsed-wave Doppler ultrasound anddirection-of-arrival estimation. I. Basic principles

Direction-of-arrival (DOA) estimation of signals is an important area of research in sonar and radar signal processing. Over the last few decades, numerous techniques have been developed for high-resolution DOA estimation. In this paper, we show that velocity measurement using pulsed-wave Doppler ultrasound and DOA estimation are isomorphic problems. We discuss a number of DOA methods and their potential application to flow velocity measurement using ultrasound. Wide-band DOA methods are of special interest because the pulses used for Doppler ultrasound are also wide band. These wide-band methods generally involve a preprocessing step to convert wideband signals to narrow band before applying high-resolution techniques. Application of DOA methods to Doppler ultrasound provides tools for high-resolution velocity measurement, identification of multiple velocity components within a sample volume, and clutter rejection     

Big Data Analytics Using Graph Signal Processing

The networks are fundamental to our modern world and they appear throughout science and society. Access to a massive amount of data presents a unique opportunity to the researcher’s community. As networks grow in size the complexity increases and our ability to analyze them using the current state of the art is at severe risk of failing to keep pace. Therefore, this paper initiates a discussion on graph signal processing for large-scale data analysis. We first provide a comprehensive overview of core ideas in Graph signal processing (GSP) and their connection to conventional digital signal processing (DSP). We then summarize recent developments in developing basic GSP tools, including methods for graph filtering or graph learning, graph signal, graph Fourier transform (GFT), spectrum, graph frequency, etc. Graph filtering is a basic task that allows for isolating the contribution of individual frequencies and therefore enables the removal of noise. We then consider a graph filter as a model that helps to extend the application of GSP methods to large datasets. To show the suitability and the effeteness, we first created a noisy graph signal and then applied it to the filter. After several rounds of simulation results. We see that the filtered signal appears to be smoother and is closer to the original noise-free distance-based signal. By using this example application, we thoroughly demonstrated that graph filtration is efficient for big data analytics.     

An FPGA-based open platform for ultrasound biomicroscopy

Ultrasound biomicroscopy (UBM) has been extensively applied to preclinical studies in small animal models. Individual animal study is unique and requires different utilization of the UBM system to accommodate different transducer characteristics, data acquisition strategies, signal processing, and image reconstruction methods. There is a demand for a flexible and open UBM platform to allow users to customize the system for various studies and have full access to experimental data. This paper presents the development of an open UBM platform (center frequency 20 to 80 MHz) for various preclinical studies. The platform design was based on a field-programmable gate array (FPGA) embedded in a printed circuit board to achieve B-mode imaging and directional pulsed-wave Doppler. Instead of hardware circuitry, most functions of the platform, such as filtering, envelope detection, and scan conversion, were achieved by FPGA programs; thus, the system architecture could be easily modified for specific applications. In addition, a novel digital quadrature demodulation algorithm was implemented for fast and accurate Doppler profiling. Finally, test results showed that the platform could offer a minimum detectable signal of 25 μV, allowing a 51 dB dynamic range at 47 dB gain, and real-time imaging at more than 500 frames/s. Phantom and in vivo imaging experiments were conducted and the results demonstrated good system performance.     

50th Anniversary Article: Comparison Studies of Full Wavefield Signal Processing for Crack Detection

The signals acquired by measurements of elastic wave propagation have been used for damage detection since the 1970s. The measurements have been carried out mostly by using piezoelectric transducers of various types. Many different sensor configurations and data processing have been proposed to detect and localise structural defects, both for real‐time and off‐line testing. Nevertheless, in the last decade, significant progress in the measurement techniques such as scanning laser Doppler vibrometry and shearographic interferometry has been made. These techniques enable measurement of a full wavefield of elastic waves. This opens up new possibilities and solutions for the problems of the damage detection in structures. Many researchers successfully applied this type of measurements for the damage detection and localisation in thin‐walled structures. Moreover, advanced signal processing techniques, such as wavenumber filtering, give the possibility of damage size estimation, by filling the gap between damage detection and damage prognosis. The aim of this paper is to give a comprehensive review of methods used for the full wavefield measurement. It also describes and compares selected signal processing algorithms developed for damage detection and visualisation based on these measuring techniques. Criticism aspects, as well as advantages of each algorithm, are denoted based on the authors' expertise in the field.     

On the performance of regression and step-initialized IIR clutterfilters for color Doppler systems in diagnostic medical ultrasound

One of the major issues in color Doppler ultrasound is the suppression of clutter that arises from stationary or slowly moving tissue. If not adequately suppressed, clutter can severely affect the ability of color Doppler systems to accurately estimate the Doppler mean frequency and power of blood, resulting in a potentially misleading depiction of flow. In this study, the performances of two classes of clutter suppression techniques-step-initialized infinite impulse response (IIR) and regression filters-were evaluated and compared by means of extensive simulations. The performance indicators used were the accuracy and precision of the mean frequency and the power estimates after clutter filtering. In summary, the ability of both filter classes to suppress clutter was found to vary considerably depending on factors such as the clutter-to-flow-signal ratio and the ensemble length. In particular, the performance of step-initialized IIR filters was shown to be noticeably inferior to that predicted by their steady-state response. Regression filters were found to offer significantly better performance than step-initialized IIR filters under heavy clutter conditions and, given their steeper roll-off, appear to be more effective clutter suppressors for power Doppler imaging. However, it should be noted that, as demonstrated by the simulations, the performance of IIR filters is severely degraded by their transient response which, in turn, is determined by the initialization scheme used. Therefore, more elaborate schemes-with superior transient characteristics than step-initialization-could significantly improve the effectiveness of IIR filtering under heavy clutter conditions