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     

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     

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.     

An elasticity microscope. Part I: Methods

An elasticity microscope images tissue stiffness at fine resolution. Possible applications include dermatology, ophthalmology, pathology, and tissue engineering. In addition, if the resolution approaches cellular dimensions, then this system may be very useful in understanding tissue micromorphology. Elasticity images can be reconstructed from displacement and strain fields measured throughout the specimen during controlled external loading. High frequency ultrasound is used to obtain these images by tracking coherent speckle motion during deformation. In this paper, methods are presented to track speckle in two dimensions with near unity correlation coefficients using a high frequency, single element focused transducer. These techniques include improved means for speckle tracking. Procedures to control boundary conditions for consistent specimen deformation and scanning techniques required to obtain a plane-strain state in the imaging plane are also discussed. To test these methods, a 50 MHz elasticity microscope was constructed     

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.     

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.     

Reduced peak-hopping artifacts in ultrasonic strain estimation using the Viterbi algorithm

Internal strain resulting from tissue deformation can be estimated by correlation processing of speckle patterns within complex (i.e., radio frequency) ultrasound images acquired during deformation. At large deformations, the magnitude of the correlation coefficient peak can be significantly lower than unity, so that random speckle correlations will exceed the true peak. This effect is called ?peak hopping? and causes significant errors in displacement and deformation estimates. Here we investigate the Viterbi algorithm, a dynamic programming procedure, to overcome peak-hopping artifacts by finding the most likely sequence of hidden states in a sequence of observed events. It is well suited to motion estimation in elasticity- imaging studies because adjacent tissue elements remain adjacent following deformation. Particularly, tissue elements along an ultrasonic beam in one image lie along a 3-D continuous curve in the next image instant. The observed event in this case is the correlation coefficient of a pixel at a certain displacement. Radio-frequency data were generated before and after deformation with an average strain of 6%. Simulations were performed for a homogenous medium and for a medium with a stiffer inclusion. Results show that Viterbi processing of speckle-tracking outputs can significantly reduce peak-hopping artifacts.     

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.     

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.     

Strain compounding: a new approach for speckle reduction

A new compounding technique for reducing speckle brightness variations is proposed. This method exploits the decorrelation between signals under different strain states. The different strain states can be created using externally applied forces such as the ones used in sonoelastography. Such forces produce three-dimensional tissue motion. By correcting only the in-plane (i.e., axial and lateral) motion, the images under different strain states have similar characteristics except for speckle appearance caused by the uncorrected out-of-plane (i.e., elevational) motion. Additional speckle decorrelation is also introduced through tissue motion correction caused by the change of effective in-plane sample volume geometry. Therefore, these images can be combined for speckle reduction with less degradation in in-plane spatial resolution than conventional approaches. In this paper, three-dimensional tissue motion under various strain conditions were simulated. It was found that significant speckle decorrelation existed at strains achievable in some clinical situations. Experiments were also conducted to test efficacy of this approach. Pulse-echo data from a gelatin-based phantom were acquired using a 5-MHz, single crystal transducer, and both conventional and compound B-mode images were formed. Results indicated that speckle brightness variations were reduced, and detectability of low contrast objects was enhanced. Performance limitations and fundamental differences between the proposed technique and existing techniques are discussed     

Ultrasonic edge shadowing around cylindrical cavities with and without walls

In B-mode ultrasound images, the speckle distal to the edges of cavities of contrasting speed of sound (SOS) can be imprinted with a pattern characteristic of the cavity. This pattern, termed edge shadowing, is likely to involve alteration of both the speckle amplitude and its correlation length. Using the acoustic field calculated from the exact solution to the wave equation, we have simulated the ensemble-averaged speckle amplitude in B-mode images of cylindrical cavities both with and without walls, and compared the results to a simpler ray-based model. The simulations show that edge shadowing is caused predominantly by contrasts of the SOS, rather than of the density. The shadows on both walled and wall-less cylinders, for a focused incident beam, grow darker as the magnitude of the SOS contrast increases over a range up to +/- 10%. Extra shadows, caused by the inner wall boundary, appear on images of walled cylinders. The ray-based model agrees well with the wave model except in the shadow regions, within which the complexity of the phenomena seems to require the wave model.     

Effects of the curvelet transform over interferometric images

One of the major challenges of the current imaging techniques is to obtain good results from images acquired with interferometric techniques. The huge complexity of these images—presence of numerous negative pixels (～50%), undesired structures introduced by the sparse sampling of the frequencial domain, noise, etc.—advises us to use multiresolution techniques to separate the different problems or features and isolate them in different scales at each resolution level. In this article, we introduce a new tool known as curvelets to work with these images. Its good properties, oriented to classify the visual information in the image depending on its elongated structures, make it an interesting tool to separate the real information from artifacts that belong to the psf sidelobes in different scales. We have decomposed, using both the Wavelet and the Curvelet transform, several interferometric images simulated and acquired with astronomical arrays of radiotelescopes, with which we cover a wide range of situations, and compared each coefficients scale obtained with both transforms. We have found that celestial sources shape keeps better its symmetry in each curvelet scale than in wavelets, and the capability of differentiation between extended sources and point ones is also higher. The identification of the sources is more clear with curvelets as well, because better with curvelets as well because of a high increase of the target enhancement respect the background in the negative pixels of the image. Furthermore, it is possible to create scales with only psf sidelobe information. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 333–353, 2010     

Parallel integral projection transform for straight electrode localization in 3-D ultrasound images

In surgical practice, small metallic instruments are frequently used to perform various tasks inside the human body. We address the problem of their accurate localization in the tissue. Recent experiments using medical ultrasound have shown that this modality is suitable for real-time visualization of anatomical structures as well as the position of surgical instruments. We propose an image-processing algorithm that permits automatic estimation of the position of a line-segment-shaped object. This method was applied to the localization of a thin metallic electrode in biological tissue. We show that the electrode axis can be found through maximizing the parallel integral projection transform that is a form of the Radon transform. To accelerate this step, hierarchical mesh-grid algorithm is implemented. Once the axis position is known, localization of the electrode tip is performed. The method was tested on simulated images, on ultrasound images of a tissue mimicking phantom containing a metallic electrode, and on real ultrasound images from breast biopsy. The results indicate that the algorithm is robust with respect to variations in electrode position and speckle noise. Localization accuracy is of the order of hundreds of micrometers and is comparable to the ultrasound system axial resolution.     

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.     

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.     

Contrast enhancement and robustness improvement of adaptive ultrasound imaging using forward-backward minimum variance beamforming

In adaptive ultrasound imaging, accurate estimation of the array covariance matrix is of great importance, and biases the performance of the adaptive beamformer. The more accurately the covariance matrix can be estimated, the better the resolution and contrast can be achieved in the ultrasound image. To this end, in this paper, we have used the forward-backward spatial averaging for array covariance matrix estimation, which is then employed in minimum variance (MV) weights calculation. The performance of the proposed forward-backward MV (FBMV) beamformer is tested on simulated data obtained using Field II. Data for two closely located point targets surrounded by speckle pattern are simulated showing the higher amplitude resolution of the FBMV beamformer in comparison to the forward-only (F-only) MV beamformers, without the need for diagonal loading. A circular cyst with a diameter of 6 mm and a phantom containing wire targets and two cysts with different diameters of 8 mm and 6 mm are also simulated. The simulations show that the FBMV beamformer, in contrast to the F-only MV, could estimate the background speckle statistics without the need for temporal smoothing, resulting in higher contrast for the FBMV-resulted image in comparison to the MV images. In addition, the effect of steering vector errors is investigated by applying an error of the sound speed estimate to the ultrasound data. The simulations show that the proposed FBMV beamformer presents a satisfactory robustness against data misalignment resulted from steering vector errors, outperforming the regularized F-only MV beamformer. These improvements are achieved without compromising the good resolution of the MV beamformer and resulted from more accurate estimation of the covariance matrix and consequently, the more accurate setting of the MV weights.     

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     

Ultrasound three-dimensional velocity measurements by featuretracking

This article describes a new angle-independent method suitable for three-dimensional (3-D) blood flow velocity measurement that tracks features of the ultrasonic speckle produced by a pulse echo system. In this method, a feature is identified and followed over time to detect motion. Other blood flow velocity measurement methods typically estimate velocity using one- (1-D) or two-dimensional (2-D) spatial and time information. Speckle decorrelation due to motion in the elevation dimension may hinder this estimate of the true 3-D blood flow velocity vector. Feature tracking is a 3-D method with the ability to measure the true blood velocity vector rather than a projection onto a line or plane. Off-line experiments using a tissue phantom and a real-time volumetric ultrasound imaging system have shown that the local maximum detected value of the speckle signal may be identified and tracked for measuring velocities typical of human blood flow. The limitations of feature tracking, including the uncertainty of the peak location and the duration of the local maxima are discussed. An analysis of the expected error using this method is given     

Large-field-of-view, modular, stabilized, adaptive-optics-based scanning laser ophthalmoscope

We describe the design and performance of an adaptive optics retinal imager that is optimized for use during dynamic correction for eye movements. The system incorporates a retinal tracker and stabilizer, a wide-field line scan scanning laser ophthalmoscope (SLO), and a high-resolution microelectromechanical-systems-based adaptive optics SLO. The detection system incorporates selection and positioning of confocal apertures, allowing measurement of images arising from different portions of the double pass retinal point-spread function (psf). System performance was excellent. The adaptive optics increased the brightness and contrast for small confocal apertures by more than 2x and decreased the brightness of images obtained with displaced apertures, confirming the ability of the adaptive optics system to improve the psf. The retinal image was stabilized to within 18 microm 90% of the time. Stabilization was sufficient for cross-correlation techniques to automatically align the images.