Time reversal processing in ultrasonic nondestructive testing

In this paper, we present a novel and completely different approach to focusing on defects beneath plane or curved surfaces: the time reversal mirror method. The time reversal technique is based on the concept of time reversal of ultrasonic fields and takes into account both the phase and modulus information coming from the defect. This technique is self-adaptative and requires only the presence of a target in the solid sample. In highly scattering media, it is shown that the time reversal process allows a new approach to speckle noise reduction. Experimental results obtained with a 121-channel time reversal mirror on titanium and duralumin samples are presented. They demonstrate the ability of time reversal to compensate for the distortions induced by liquid-solid interfaces of different geometries and to detect small defects in a noisy background     

Real-time ultrasound simulation using the GPU

Ultrasound simulators can be used for training ultrasound image acquisition and interpretation. In such simulators, synthetic ultrasound images must be generated in real time. Anatomy can be modeled by computed tomography (CT). Shadows can be calculated by combining reflection coefficients and depth dependent, exponential attenuation. To include speckle, a pre-calculated texture map is typically added. Dynamic objects must be simulated separately. We propose to increase the speckle realism and allow for dynamic objects by using a physical model of the underlying scattering process. The model is based on convolution of the point spread function (PSF) of the ultrasound scanner with a scatterer distribution. The challenge is that the typical field-of-view contains millions of scatterers which must be selected by a virtual probe from an even larger body of scatterers. The main idea of this paper is to select and sample scatterers in parallel on the graphic processing unit (GPU). The method was used to image a cyst phantom and a movable needle. Speckle images were produced in real time (more than 10 frames per second) on a standard GPU. The ultrasound images were visually similar to images calculated by a reference method.     

Spatio-temporal coding in complex media for optimum beamforming: the iterative time-reversal approach

Spatio-temporal encoding in transmit and receive modes is of major importance in the development of ultrasound imaging devices. Classically, the assumption of constant sound speed in the medium allows one to restrict the beamforming process to the application of a cylindrical time-delay law on the elements of a multiple-transducer array. Here is proposed an iterative time-reversal method capable of taking into account all the heterogeneities of the medium, concerning density, speed of sound, and absorption variations. It will be shown that this iterative focusing process converges toward a spatio-temporal inverse filter focusing, the first step of the process being a time-reversal focusing on the targeted point. This method can be seen as a calibration process and has been successfully applied to transskull focusing and intraplate echoes suppression. It is leading the way to promising applications such as high-resolution ultrasonic brain imaging and high-resolution focusing through complex reverberating media, in nondestructive testing and telecommunications. This work highlights the advantages of using spatio-temporal coding to focus through complex media. Such codes require the use of fully programmable, multichannel electronics to implement this technique in real time.     

基于K-wave的经颅超声聚焦仿真研究

由于颅骨形状不规则，声速、密度等声学参数分布不均匀，使用传统相控聚焦的方法进行经颅超声精确聚焦时会出现焦点偏移、焦点形状畸变、散焦的现象，时间反转法被认为是能够克服颅骨非均匀特性，实现经颅聚焦的有效手段。而利用传统有限元，有限差分法进行数值仿真时，往往需要划分十分精密的网格进行计算，耗费大量的时间。K空间伪谱法通过在空间域上进行傅里叶变换，时间域上进行有限差分的方法求解声波方程，能够在降低计算网格密度的同时保证计算精度。为了克服颅骨对聚焦超声造成的焦移影响，同时避免声学模型计算量过大的问题，本文使用Matlab K-wave开源工具箱，对食蟹猴颅骨CT数据进行三维声学建模，实现了基于时间反转法的经颅超声聚焦，讨论了时间反转法对于颅骨不规则形状及非均匀声速造成的焦移的补偿。仿真结果表明，K-wave在提高计算速度的同时能够服务于精准经颅超声聚焦，且相较于传统基于声时差法的相控聚焦方法，时间反转法在预设焦点位置，焦点强度更高，焦斑形状更为规则，聚焦效果更好。     

Ultrasonic beam steering through inhomogeneous layers with a timereversal mirror

Adaptive time delay focusing techniques allow an efficient correction of the effects due to an inhomogeneous layer close to the transducer array. If the layer is far from the array, these techniques are no longer appropriate to correct the diffraction effects between the layer and the transducer array. This problem was overcome by the use of acoustic time reversal mirrors. In this technique, the Green's function of a dominant scatterer available in the medium is recorded in digital memories and used to focus on the scatterer in both transmit and receive modes. We present in this paper an extension of this technique to focus, in the presence of an aberrating layer, not only on the dominant scatterer, but also around it in order to image the surrounding zone. From the knowledge of the Green's function needed to focus on the initial scatterer, we calculate the new Green's function matched to the new point of interest. The algorithm uses the concept of time reversal propagation, and we shall present here theoretical and experimental results obtained with this technique. Finally, the knowledge of each Green's function matched to each new desired focal point allows the realization of a B-scan image of the zone surrounding the reflector     

An approach to multibeam covariance matrices for adaptive beamforming in ultrasonography

Medical ultrasound imaging systems are often based on transmitting, and recording the backscatter from, a series of focused broadband beams with overlapping coverage areas. When applying adaptive beamforming, a separate array covariance matrix for each image sample is usually formed. The data used to estimate any one of these covariance matrices is often limited to the recorded backscatter from a single transmitted beam, or that of some adjacent beams through additional focusing at reception. We propose to form, for each radial distance, a single covariance matrix covering all of the beams. The covariance matrix is estimated by combining the array samples after a sequenced time delay and phase shift. The time delay is identical to that performed in conventional delay-and-sum beamforming. The performance of the proposed approach in conjunction with the Capon beamformer is studied on both simulated data of scenes consisting of point targets and recorded ultrasound phantom data from a specially adapted commercial scanner. The results show that the proposed approach is more capable of resolving point targets and gives better defined cyst-like structures in speckle images compared with the conventional delay-and-sum approach. Furthermore, it shows both an increased robustness to noise and an increased ability to resolve point-like targets compared with the more traditional per-beam Capon beamformer.     

Reconstructing two-dimensional acoustic object fields by use of digital phase conjugation of scanning laser vibrometry recordings

A scanning laser Doppler vibrometer is used to record two-dimensional ultrasound fields in air. The laser light of the vibrometer traverses the sound field to and from a rigid reflector and determines the velocity field, a quantity proportional to the sound pressure rate, in each scanned point relative to the sound source. The object sound is the scattered field from objects outside the recording area. Digital reconstruction by use of phase conjugation (time reversal) of the object sound field is then performed, and the original object field intensity and phase is reconstructed.     

Superresolution of ultrasound images using the first and second harmonic signal

This paper presents a new method of blind two-dimensional (2-D) homomorphic deconvolution and speckle reduction applied to medical ultrasound images. The deconvolution technique is based on an improved 2-D phase unwrapping scheme for pulse estimation. The input images are decomposed into minimum-phase and allpass components. The 2-D phase unwrapping is applied only to the allpass component. The 2-D phase of the minimum-phase component is derived by a Hilbert transform. The accuracy of 2-D phase unwrapping is also improved by processing small (16 x 16 pixels) overlapping subimages separately. This takes the spatial variance of the ultrasound pulse into account. The deconvolution algorithm is applied separately to the first and second harmonic images, producing much sharper images of approximately the same resolution and different speckle patterns. Speckle reduction is made by adding the envelope images of the deconvolved first and second harmonic images. Neither the spatial resolution nor the frame rate decreases, as the common compounding speckle reduction techniques do. The method is tested on sequences of clinical ultrasound images, resulting in high-resolution ultrasound images with reduced speckle noise.     

被动迭代时间反转镜研究

抗除多途信道的干扰,优化被动检测性能是声纳信号处理关注的问题之一。通过仿真揭示了多途信道中单水听器时间反转镜的聚焦效应,研究了被动迭代时间反转镜技术,对其多目标定位选择性、多目标选择聚焦性能作了研究。结果表明利用了海洋信道的相干多途特性,被动时间反转镜可实现多个目标的空间匹配滤波：利用迭代算法,被动迭代时间反转镜可在抑制环境噪声干扰的同时,在信道输出总能量强的目标处实现选择性聚焦。     

A speckle target adaptive imaging technique in the presence of distributed aberrations

Acoustic velocity inhomogeneities in tissue result in aberration of ultrasound images. These aberrations can be modeled as a near field thin phase screen or as a distributed aberrator. The effect of a near field thin phase screen is to time shift the received echo at each element, while distributed aberrators result in both pulse distortions and time shifts from element to element. Most current techniques for the correction of distributed aberrators are limited to application on point targets. A new technique is proposed which uses multiple transmits from spatially shifted transmit apertures (the translating transmit aperture algorithm), in conjunction with phase conjugate filters, to correct for distributed aberrations in the presence of speckle targets. The performance of the translating transmit aperture algorithm in improving the correlation between signals received by elements of different spatial separations is measured, and factors affecting the performance of this technique are investigated in simulation and experiment.     

Ultrasound Speckle Reduction Based on Histogram Curve Matching and Region Growing

The quality of ultrasound scanning images is usually damaged by speckle noise. This paper proposes a method based on local statistics extracted from a histogram to reduce ultrasound speckle through a region growing algorithm. Unlike single statistical moment-based speckle reduction algorithms, this method adaptively smooths the speckle regions while preserving the margin and tissue structure to achieve high detectability. The criterion of a speckle region is defined by the similarity value obtained by matching the histogram of the current processing window and the reference window derived from the speckle region in advance. Then, according to the similarity value and tissue characteristics, the entire image is divided into several levels of speckle-content regions, and adaptive smoothing is performed based on these classification characteristics and the corresponding window size determined by the proposed region growing technique. Tests conducted from phantoms and in vivo images have shown very promising results after a quantitative and qualitative comparison with existing work.     

The effect of including myocardial anisotropy in simulated ultrasound images of the heart

We have examined the effect of incorporating tissue anisotropy in simulated ultrasound images of the heart. In simulation studies, the cardiac muscle (myocardium) is usually modeled as a cloud of uncorrelated point scatterers. Although this approach successfully generates a realistic speckle pattern, it fails to reproduce any effects of image anisotropy seen in real ultrasound images. We hypothesize that some of this effect is caused by the varying orientation of anisotropic myocardial structures relative to the ultrasonic beam and that this can be taken into account in simulations by imposing an angle dependent correlation of the scatterer points. Ultrasound images of a porcine heart were obtained in vitro, and the dominating fiber directions were estimated from the insonification angles that gave rise to the highest backscatter intensities. A cylindrical sample of the myocardium was then modeled as a grid of point scatterers correlated in the principal directions of the muscle fibers, as determined experimentally. Ultrasound images of the model were simulated by using a fast k-space based convolution approach, and the results were compared with the in vitro recordings. The simulated images successfully reproduced the insonification dependent through-wall distribution of backscatter intensities in the myocardial sample, as well as a realistic speckle pattern.     

Markov models of specular and diffuse scattering in restoration ofmedical ultrasound images

Observed medical ultrasound images are degraded representations of the true tissue reflectance. The specular reflections at boundaries between regions of different tissue types are blurred, and the diffuse scattering within such regions also contains speckle. This reduces the diagnostic value of such images. In order to remove both blur and speckle, the authors develop a maximum a posteriori deconvolution algorithm for two-dimensional (2-D) ultrasound radio frequency (RF) images based on a new Markov random field image model incorporating spatial smoothness constraints and physical models for specular reflections and diffuse scattering. During stochastic relaxation, the algorithm alternates steps of restoration and segmentation, and includes estimation of reflectance parameters. The smoothness constraints regularize the overall procedure, and the algorithm uses the specular reflection model to locate region boundaries. The resulting restorations of some simulated and real RF images are significantly better than those produced by Wiener filtering     

基于自适应形态滤波的医学超声图像降噪

针对医学超声图像上的斑点噪声,本文提出一种基于自适应形态滤波的降噪方法.首先构造一组检测图像中不同像素值突变的结构因子;再对每个结构因子构造相应的形态滤波结构元;最后对每个像素点邻域进行结构检测,找到该点处最可能存在的突变结构,以相应的结构元完成该点的形态滤波.对不同信噪比的仿真图像和实际图像分别采用本文方法和各向异性扩散滤波,不同尺度传统形态滤波进行了:比较实验,结果表明:采用本方法可将超声图像的信噪比、对比度噪声比和图像优度分别平均提高15%、37%和69%,优于其它方法.     

Poisson noise reduction from X-ray images by region classification and response median filtering

Medical imaging is perturbed with inherent noise such as speckle noise in ultrasound, Poisson noise in X-ray and Rician noise in MRI imaging. This paper focuses on X-ray image denoising problem. X-ray image quality could be improved by increasing dose value; however, this may result in cell death or similar kinds of issues. Therefore, image processing techniques are developed to minimise noise instead of increasing dose value for patient safety. In this paper, usage of modified Harris corner point detector to predict noisy pixels and responsive median filtering in spatial domain is proposed. Experimentation proved that the proposed work performs better than simple median filter and moving average (MA) filter. The results are very close to non-local means Poisson noise filter which is one of the current state-of-the-art methods. Benefits of the proposed work are simple noise prediction mechanism, good visual quality and less execution time.     

Speckle motion artifact under tissue rotation

Speckle patterns in ultrasound images may move in a way which bears no simple relationship to the motion of the corresponding tissues. In some instances the speckle motion replicates the underlying tissue motion, in others it does not. The authors name “speckle motion artifact” the difference between the speckle and the underlying tissue motion. An echographic image formation model is used to study the motion artifact produced by a rotating phantom and observed by a linear scan imaging system with a Gaussian beam. The authors propose that when the tissue is modeled as a random array of small and numerous scatterers, such motion aberration be accounted for by the 2D phase characteristics of the imaging system. An analytic prediction of this motion artifact in relation to the imaging system characteristics (beam width, transducer frequency, pulse duration) is presented. It is shown that the artifact results from the curvature of the system point spread function, which in turn determines the curvature of the 2D phase characteristics. To the authors' knowledge, it is the first time a comprehensive model of ultrasonic speckle motion artifact is presented. The model has been developed to study rotation-induced artifact; the method is however quite general and can be extended to study the effects of other tissue motion, in particular deformation and shear     

Ultrasound speckle reduction using modified Gabor filters

B-mode ultrasound images are characterized by speckle artifact, which may make the interpretation of images difficult. One widely used method for ultrasound speckle reduction is the split spectrum processing (SSP), but the use of one-dimensional (1-D), narrow-band filters makes the resultant image experience a significant resolution loss. In order to overcome this critical drawback, we propose a novel method for speckle reduction in ultrasound medical imaging, which uses a bank of wideband 2-D directive filters, based on modified Gabor functions. Each filter is applied to the 2-D radio-frequency (RF) data, resulting in a B-mode image filtered in a given direction. The compounding of the filters outputs give rise to a final image in which speckle is reduced and the structure is enhanced. We have denoted this method as directive filtering (DF). Because the proposed filters have effectively the same bandwidth as the original image, it is possible to avoid the resolution loss caused by the use of narrow-band filters, as with SSP. The tests were carried out with both simulated and real clinical data. Using the signal-to-noise ratio (SNR) to quantify the amount of speckle of the ultrasound images, we have achieved an average SNR enhancement of 2.26 times with simulated data and 1.18 times with real clinical data.     

Speckle interferometry by using virtual speckle pattern based on Carré algorithm

Dynamic deformation measurement with a large deformation is effectively performed by using virtual speckle patterns. The virtual speckle pattern has been generally produced by using the operation based on Fourier transform. However, it takes a long calculating time to produce a virtual speckle pattern, because the method requires Fourier transform operation at each pixel of CCD. In the proposed method, virtual speckle patterns are produced by Carré algorithm without any operation by Fourier transform. The method is applied to the in-plane deformation measurement in this paper. As the results, it is confirmed that the calculating cost of virtual speckle patterns is improved remarkably, and that the measurement accuracy of the new method is also equal to the ordinary methods. It is also confirmed that the proposed method will expand the use of the speckle interferometry based on virtual speckle pattern technology.     

A frequency domain model for generating B-mode images with array transducers

A frequency domain B-mode imaging model applicable to linear and phased array transducers was developed for simulating ultrasound images of random media. Computations are based on an approximation that is less restrictive than the Fresnel approximation. The model is compared with the exact time domain impulse response method, regarded as the "gold standard". In a typical application, errors in simulated rf waveforms are less than 1% regardless of the steering angle for distances greater than 2 cm, yet computation times are on the order of 1/150 of those using the exact method. This model takes into account the effects of frequency-dependent attenuation, backscattering, and dispersion. Modern beam-forming techniques such as apodization, dynamic aperture, elevational focusing, multiple transmit focusing and dynamic receiving focusing also can be simulated.     

Bayesian 2-D deconvolution: a model for diffuse ultrasound scattering

Observed medical ultrasound images are degraded representations of the true acoustic tissue reflectance. The degradation is due to blur and speckle and significantly reduces the diagnostic value of the images. To remove both blur and speckle, we have developed a new statistical model for diffuse scattering in 2-D ultrasound radio frequency images, incorporating both spatial smoothness constraints and a physical model for diffuse scattering. The modeling approach is Bayesian in nature, and we use Markov chain Monte Carlo methods to obtain the restorations. The results from restorations of some real and simulated radio frequency ultrasound images are presented and compared with results produced by Wiener filtering