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.     

Ultrasound speckle reduction using harmonic oscillator models

A speckle reduction algorithm called the harmonic imaging (HI) algorithm is presented. It is based on a multicomponent scattering model for medical ultrasonics. The backscattered ultrasound quadrature signal is modeled as the sum of three components after demodulation. The first component represents nonresolvable diffuse scatterers, while the second component represents subresolvable quasi-periodic scatterers. The third component represents resolvable quasi-periodic scatterers and mirroring surfaces. Since the second component gives rise to the most long range destructive interference effects it is eliminated in the HI algorithm to reduce speckle. Due to its slow spatial variation, it can be almost completely eliminated simply by differentiating the backscattered demodulated quadrature signal. Lissajous-like figures are observed in complex plots of the signals from ultrasound beams going through tissues with quasi-periodic components and sometimes in areas with only diffuse scatterers. Therefore the sum of the complex signals from the resolvable and nonresolvable scatterers within a resolution cell is modeled by two orthogonal and independent harmonic oscillators. The estimated, total energy of these two oscillators determines the gray level value of the HI image within the resolution cell. The HI images produced using radio frequency data from a phantom and from tissues in vivo are more blurred than ordinary envelope images, but the signal to noise ratio and tissue contrast were higher for the HI images     

Toward a real-time simulation of ultrasound image sequences based on a 3-D set of moving scatterers

Data simulation is an important research tool to evaluate algorithms. Two types of methods are currently used to simulate medical ultrasound data: those based on acoustic models and those based on convolution models. The simulation of ultrasound data sequences is very time-consuming. In addition, many applications require accounting for the out-ofplane motion induced by the 3-D displacement of scatterers. The purpose of this paper is to propose a model adapted to a fast simulation of ultrasonic data sequences with 3-D moving scatterers. Our approach is based on the convolution model. The scatterers are moved in a 3-D continuous medium between each pair of images and then projected onto the imaging plane before being convolved. This paper discusses the practical implementation of the convolution that can be performed directly or after a grid approximation. The grid approximation convolution is obviously faster than the direct convolution but generates errors resulting from the approximation to the grid?s nodes. We provide the analytical expression of these errors and then define 2 intensity-based criteria to quantify them as a function of the spatial sampling. The simulation of an image requires less than 2 s with oversampling, thus reducing these errors. The simulation model is validated with first- and second-order statistics. The positions of the scatterers at each imaging time can be provided by a displacement model. An example applied to flow imaging is proposed. Several cases are used to show that this displacement model provides realistic data. It is validated with speckle tracking, a well-known motion estimator in ultrasound imaging.     

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     

Superposition of Two Dynamic Speckle Patterns

Abstract

A model is proposed to explain the influence of blood flow and moving surrounding tissue on laser light scattering. Blood and tissue are represented by two sets of scatterers which are moving in arbitrary directions with different velocities. The real dynamic speckle pattern is thought to be composed of the coherent superposition of the two speckle patterns due to the scattering on these two sets of scatterers. The model describes the spectrum of the speckle intensity in an arbitrary observation point. No special assumptions must be made concerning the geometry of illumination and the position of the observation point. A measuring value B for the determination of the blood flow is derived from the speckle intensity. The model also provides the dependence of B on density and mean velocity of each set of scatterers. It has been shown that the main contribution of the tissue movement on B can be compensated by a control measurement and that the sensitivity of B due to blood velocity variations depends on the density of both sets of scatterers and on the tissue velocity.     

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.     

Aberration correction by time reversal of moving speckle noise

Focusing a wave through heterogeneous media is an important problem in medical ultrasound imaging. In such aberrating media, in the presence of a small number of point reflectors, iterative time reversal is a well-known method able to focus on the strongest reflector. However, in presence of speckle noise generated by many non-resolved scatterers, iterative time reversal alone does not work. In this paper, we propose the use of the echoes coming from moving particles in a flow, such as red blood cells, to generate a virtual point reflector by iterative time reversal. The construction of the virtual point reflector is performed by a coherent addition of independent realizations of speckle coming from moving particles. After focusing on a virtual point reflector, ultrasound images can be locally corrected inside an isoplanatic patch. An application for the correction of power Doppler images is presented. A theoretical analysis shows that this iterative method allows focusing on the point of maximal insonification of the uncorrected beam.     

Discriminating real objects in radar imaging by exploiting the squared modulus of the continuous wavelet transform

New technique based on continuous wavelet transform (CWT) for classifying objects in synthetic aperture radar (SAR) imaging is presented. The CWT allows to analyse two-dimensional SAR images to highlight the frequency and angular behaviour of the scatterers. This technique allows to build a SAR hyperimage, that is, a four-dimensional data cube which represents for each spatial location (x, y) of the scatterer in the image, its frequency and angular energy behaviour. When analysing different targets, objects or areas in SAR images, it has been recently observed that some scatterers belonging to a same class of objects could have similar frequency and angular energy responses. The previous observations have motivated the determination to exploit these energy responses to discriminate these objects. This discrimination is performed by frequency and angular correlations between the response of a particular scatterer (measured) and those of all the scatterers in the SAR image. Some examples of discrimination from real SAR data are presented and show an interest of the method for target classification and recognition for SAR imaging     

Tissue stiffness imaging method using temporal variation of ultrasound speckle pattern

Applying vibration to a medium makes it vibrate. The resulting change in scatterer distribution inside the medium due to applied vibration changes the speckle pattern of ultrasound images. In this case, scatterers in a hard medium experience small displacements, and those in a soft medium experience large displacements. As a result, the amount of speckle pattern brightness change in ultrasound images is related to the tissue stiffness. Using this dependency, a two-dimensional profile of relative tissue stiffness can be constructed qualitatively at the display pixel resolution by determining at each pixel the standard deviation and/or the difference between minimum and maximum values over a certain number of consecutive B-mode images. Experiments with phantoms show that the softer the tissue, the larger the standard deviation. The proposed imaging modality is a simple yet practical method of resolving hard cysts surrounded by soft background in a phantom using B-mode frame data only.     

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.     

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     

Corrosion monitoring with speckle correlation

The changes in the microtopography of a metal surface during a corrosion process are measured by decorrelation of the scattered speckle fields under coherent illumination. For that purpose a quantitative relation between the decorrelation of the scattered light fields and the rate of corrosion is established in a theoretical model, based on the statistics of phase and reflectivity changes of point scatterers at the surface. The speckle fields are recorded by a CCD camera and processed numerically in a computer, yielding the standard deviation of the topography changes with nanometer sensitivity. From the analysis of a series of images taken at equal time intervals during the corrosion process, the degree of interrelation among subsequent topography changes is calculated.     

Deep-space satellite-image reconstructions from field data by use of speckle imaging techniques: images and functional assessment

Speckle imaging techniques have been shown to mitigate atmospheric-resolution limits, allowing near-diffraction-limited images to be reconstructed. Few images of extended objects reconstructed by use of these techniques have been published, and most of these results are for relatively bright objects. We present image reconstructions of an orbiting Molniya 3 spacecraft from data collected by use of a 2.3-m ground-based telescope. The apparent brightness of the satellite was 15th visual magnitude. Power-spectrum and bispectrum speckle imaging techniques are used prior to image reconstruction to ameliorate atmospheric blurring. We discuss how these images, although poorly resolved, can be used to provide information on the satellite's functional status. It is shown that our previously published optimal algorithms produce a higher-quality image than do conventional speckle imaging methods.     

Comparison of speckle reduction diversity tools for active millimeter-wave imaging

Imaging concealed objects with millimeter-wave coherent radiation is accompanied by speckle. Like all interference phenomena, speckle depends on three light parameters of the millimeter-wave laser beam--phase, wavelength, and angle of incidence--and can be reduced by the diversity of these three parameters. Diversity tools to improve images of concealed objects have been compared. We report measurements, simulations, and image reconstruction results over the whole W-band (75-110 GHz) and demonstrate where each tool works the best. Multiphase diversity is successful in reducing speckle contrast: multiangle to improve the image quality, and multispectral to recognize a small object's features. A simple postprocessing eliminates the areas still covered by interference.     

Speckle reduction by I-divergence regularization in optical coherence tomography

For optical coherence tomography (OCT), ultrasound, synthetic-aperture radar, and other coherent ranging methods, speckle can cause spurious detail that detracts from the utility of the image. It is a problem inherent to imaging densely scattering objects with limited bandwidth. Using a method of regularization by minimizing Csiszar's I-divergence measure, we derive a method of speckle minimization that produces an image that both is consistent with the known data and extrapolates additional detail based on constraints on the magnitude of the image. This method is demonstrated on a test image and on an OCT image of a Xenopus laevis tadpole.     

Lateral blood flow velocity estimation based on ultrasound speckle size change with scan velocity

Conventional (Doppler-based) blood flow velocity measurement methods using ultrasound are capable of resolving the axial component (i.e., that aligned with the ultrasound propagation direction) of the blood flow velocity vector. However, these methods are incapable of detecting blood flow in the direction normal to the ultrasound beam. In addition, these methods require repeated pulse-echo interrogation at the same spatial location. A new method has been introduced which estimates the lateral component of blood flow within a single image frame using the observation that the speckle pattern corresponding to blood reflectors (typically red blood cells) stretches (i.e., is smeared) if the blood is moving in the same direction as the electronically-controlled transducer line selection in a 2-D image. The situation is analogous to the observed distortion of a subject photographed with a moving camera. The results of previous research showed a linear relationship between the stretch factor (increase in lateral speckle size) and blood flow velocity. However, errors exist in the estimation when used to measure blood flow velocity. In this paper, the relationship between speckle size and blood flow velocity is investigated further with both simulated flow data and measurements from a blood flow phantom. It can be seen that: 1) when the blood flow velocity is much greater than the scan velocity (spatial rate of A-line acquisition), the velocity will be significantly underestimated because of speckle decorrelation caused by quick blood movement out of the ultrasound beam; 2) modeled flow gradients increase the average estimation error from a range between 1.4% and 4.4%, to a range between 4.4% and 6.8%; and 3) estimation performance in a blood flow phantom with both flow gradients and random motion of scatterers increases the average estimation error to between 6.1% and 7.8%. Initial attempts at a multiple-scan strategy for estimating flow by a least-squares model suggest the possibility of increased accuracy using multiple scan velocities.     

Phase-aberration correction using signals from point reflectors and diffuse scatterers: measurements

A method for phase-aberration correction of phased-array images is tested using a model of near-field velocity inhomogeneities. A set of grooved room-temperature vulcanizing plates was constructed to simulate near-field aberrations encountered in clinical ultrasound imaging. As expected, large image distortion was experienced when grooved plates producing significant aberrations were placed near the surface of the array. An iterative aberration correction procedure based on cross-correlation measures between neighboring elements in a phased array, using signals reflected from diffuse scatterers, significantly reduced the effects of these aberrations, producing images nearly identical to those generated in the absence of aberrations. The results suggest that a practical phase-aberration correction system can be constructed for medical ultrasound imaging and possibly all coherent imaging systems by using a sampled aperture.     

Wavelet restoration of medical pulse-echo ultrasound images in an EM framework

The clinical utility of pulse-echo ultrasound images is severely limited by inherent poor resolution that impacts negatively on their diagnostic potential. Research into the enhancement of image quality has mostly been concentrated in the areas of blind image restoration and speckle removal, with little regard for accurate modeling of the underlying tissue reflectivity that is imaged. The acoustic response of soft biological tissues has statistics that differ substantially from the natural images considered in mainstream image processing: although, on a macroscopic scale, the overall tissue echogenicity does behave some-what like a natural image and varies piecewise-smoothly, on a microscopic scale, the tissue reflectivity exhibits a pseudo-random texture (manifested in the amplitude image as speckle) due to the dense concentrations of small, weakly scattering particles. Recognizing that this pseudorandom texture is diagnostically important for tissue identification, we propose modeling tissue reflectivity as the product of a piecewise-smooth echogenicity map and a field of uncorrelated, identically distributed random variables. We demonstrate how this model of tissue reflectivity can be exploited in an expectation-maximization (EM) algorithm that simultaneously solves the image restoration problem and the speckle removal problem by iteratively alternating between Wiener filtering (to solve for the tissue reflectivity) and wavelet-based denoising (to solve for the echogenicity map). Our simulation and in vitro results indicate that our EM algorithm is capable of producing restored images that have better image quality and greater fidelity to the true tissue reflectivity than other restoration techniques based on simpler regularizing constraints.