Effects of red blood cell aggregates dissociation on the estimation of ultrasound speckle image velocimetry

Ultrasound speckle image of blood is mainly attributed by red blood cells (RBCs) which tend to form RBC aggregates. RBC aggregates are separated into individual cells when the shear force is over a certain value. The dissociation of RBC aggregates has an influence on the performance of ultrasound speckle image velocimetry (SIV) technique in which a cross-correlation algorithm is applied to the speckle images to get the velocity field information. The present study aims to investigate the effect of the dissociation of RBC aggregates on the estimation quality of SIV technique. Ultrasound B-mode images were captured from the porcine blood circulating in a mock-up flow loop with varying flow rate. To verify the measurement performance of SIV technique, the centerline velocity measured by the SIV technique was compared with that measured by Doppler spectrograms. The dissociation of RBC aggregates was estimated by using decorrelation of speckle patterns in which the subsequent window was shifted as much as the speckle displacement to compensate decorrelation caused by in-plane loss of speckle patterns. The decorrelation of speckles is considerably increased according to shear rate. Its variations are different along the radial direction. Because the dissociation of RBC aggregates changes ultrasound speckles, the estimation quality of SIV technique is significantly correlated with the decorrelation of speckles. This degradation of measurement quality may be improved by increasing the data acquisition rate. This study would be useful for simultaneous measurement of hemodynamic and hemorheological information of blood flows using only speckle images.     

DSPI strain measurement on an externally reinforced bending beam: A comparison of step-by-step addition and pixel shift correlation

A small-scale concrete beam reinforced with an adhesively bonded carbon fiber reinforced polymer (CFRP) plate was subjected to four-point bending. Finite element analyses (FEA) of the bending deformations were carried out to predict strain gradients near the end of the CFRP plate. In order to measure these strains, phase-stepping 3D-digital speckle pattern interferometry was employed. To avoid speckle decorrelation due to the inevitable rigid body motion of the specimen, the load was increased in small increments. Two evaluation schemes for the electronic speckle pattern interferometry phase maps are compared: summing up the measured displacement components load step-by-load step versus regain of the correlation by shifting the final image by an integer number of pixels. Measured strain values are evaluated using a polynomial fit to the measured in-plane displacements and are compared to the FE predicitions. It can be concluded that pixel shift correlation is preferable to summing up load steps for cases of large rigid body motion.     

Weak signal direction of arrival estimation for colocated multiple-input multiple-output sonar array

In order to suppress the influence of symmetrical noise component on multiple-input multiple-output(MIMO)sonar's direction of arrival(DOA)estimation under the condition of low signal-to-noise ratio,we propose a DOA estimation algorithm based on covariance matrix reconstruction method.Firstly,the noise field can be decomposed into symmetrical noise field and asymmetrical noise field.We utilize symmetry property of colored noise matrix and the feature that the imaginary part of covariance matrix has no relation with the symmetry noise to remove the real part of covariance matrix.This operation helps to suppress the influence of colored noise on DOA estimation accuracy.Based on the principle of the imaginary matrix part displacement and the dimension reduction transformation method,the real part of covariance matrix is reconstructed,which helps to suppress the bilateral spectrum interference.Thereafter,Toeplitz method is applied for the covariance matrix decorrelation amendment,and a noise subspace is formed by singular value decomposition(SVD).Finally,we can estimate the DOA of target signals.Both theoretical analysis results and numerical simulation results verify the symmetrical noise suppression performance of this algorithm,and the estimation performance of target azimuth is improved obviously.This method has the characteristics of lower operational complexity,higher degrees of freedom and stronger target resolution.     

Principal component analysis of shear strain effects

Shear stresses are always present during quasi-static strain imaging, since tissue slippage occurs along the lateral and elevational directions during an axial deformation. Shear stress components along the axial deformation axes add to the axial deformation while perpendicular components introduce both lateral and elevational rigid motion and deformation artifacts into the estimated axial and lateral strain tensor images. A clear understanding of these artifacts introduced into the normal and shear strain tensor images with shear deformations is essential. In addition, signal processing techniques for improved depiction of the strain distribution is required. In this paper, we evaluate the impact of artifacts introduced due to lateral shear deformations on the normal strain tensors estimated by varying the lateral shear angle during an axial deformation. Shear strains are quantified using the lateral shear angle during the applied deformation. Simulation and experimental validation using uniformly elastic and single inclusion phantoms were performed. Variations in the elastographic signal-to-noise and contrast-to-noise ratios for axial deformations ranging from 0% to 5%, and for lateral deformations ranging from 0 to 5° were evaluated. Our results demonstrate that the first and second principal component strain images provide higher signal-to-noise ratios of 20 dB with simulations and 10 dB under experimental conditions and contrast-to-noise ratio levels that are at least 20 dB higher when compared to the axial and lateral strain tensor images, when only lateral shear deformations are applied. For small axial deformations, the lateral shear deformations significantly reduces strain image quality, however the first principal component provides about a 1–2 dB improvement over the axial strain tensor image. Lateral shear deformations also significantly increase the noise level in the axial and lateral strain tensor images with larger axial deformations. Improved elastographic signal and contrast-to-noise ratios in the first principal component strain image are always obtained for both simulation and experimental data when compared to the corresponding axial strain tensor images in the presence of both axial and lateral shear deformations.     

A subpixel motion estimation algorithm based on digital correlation for illumination variant and noise image sequences

One of the challenges in practical subpixel motion estimation is how to obtain high accuracy with sufficient robustness to both illumination variations and additive noise. Motivated by the fact that the normalized spatial cross-correlation is invariant to illumination, we introduce a gradient-based subpixel registration method by maximizing the digital correlation (DC) function between the reference and target frames. Such DC function is remodeled with the presence of image noise, yielding that the correlation coefficient is only sensitive to noise standard variance. To fairly suppress the noise corruption, not only the target frame but also the reference one is reformulated into Taylor gradient expression with half but opposite motion vector. The final solution to motion estimates can be approximated into a closed form by reserving first-order coefficient terms of unregistered motion variables. The error trend of approximated solution is discussed. Computer simulations and actual experiments’ results demonstrate the superiority of the proposed method to the LMSE-based method and ordinary DC method when illumination variations and noise exist. Among the experiments, the influences of real subpixel translation value and noise variance degree on accuracy are studied; correspondingly, an optimized iterative idea for big translations and the recommended noise level adaptive to our method are introduced.     

Motion estimation of magnetic resonance cardiac images using the Wigner-Ville and hough transforms

Myocardial motion analysis and quantification is of utmost importance for analyzing contractile heart abnormalities and it can be a symptom of a coronary artery disease. A fundamental problem in processing sequences of images is the computation of the optical flow, which is an approximation of the real image motion. This paper presents a new algorithm for optical flow estimation based on a spatiotemporal-frequency (STF) approach. More specifically it relies on the computation of the Wigner-Ville distribution (WVD) and the Hough Transform (HT) of the motion sequences. The latter is a well-known line and shape detection method that is highly robust against incomplete data and noise. The rationale of using the HT in this context is that it provides a value of the displacement field from the STF representation. In addition, a probabilistic approach based on Gaussian mixtures has been implemented in order to improve the accuracy of the motion detection. Experimental results in the case of synthetic sequences are compared with an implementation of the variational technique for local and global motion estimation, where it is shown that the results are accurate and robust to noise degradations. Results obtained with real cardiac magnetic resonance images are presented. The text was submitted by the authors in English.     

Rotational motion in sensorless freehand three-dimensional ultrasound

Freehand three-dimensional ultrasound is usually acquired with a position sensor attached to the ultrasound probe. However, position sensors can be expensive, obtrusive and difficult to calibrate. For this reason, there has been much research on alternative, image-based techniques, with in-plane motion tracked using conventional image registration methods, and out-of-plane motion inferred from the decorrelation between nearby B-scans. However, since out-of-plane motion is not the only source of decorrelation, image-based positions determined in this way suffer from cumulative drift errors. In this paper, we consider the effect of probe rotation on correlation and how this affects the position estimates. We then present a novel technique to compensate for out-of-plane rotations, by making use of orientation measurements from an unobtrusive sensor. Using simulations and in vitro experiments, we demonstrate that the technique is able to reduce the drift error in elevational positioning by 57% on average.     

结合生物力学模型重建左心室位移场

左心室心肌最为发达,心肌收缩产生的高压将动脉血泵入全身,集中体现了心脏的泵血能力.定量分析左心室收缩运动是诊断心血管疾病（如心肌梗死）的重要途径.本文采用描述左心室心肌材质的生物力学模型重建左心室位移场.该力学模型作为插值项,与心脏电影磁共振图像的观测位移场共同纳入贝叶斯估计框架,并采用有限元法求解位移场方程.实验比较了左心室射血无力组（46例）与正常组（55例）的左心室功能参数,发现两组在径向和圆周方向的位移、速度、应变和应变率都具有非常显著的差异（p < 0.001）,这证明本文方法能够有效区别左心室运动正常与否.实验结果还与CVI软件测量的左心室功能参数具有较高的相关性,说明本文方法有望辅助心血管疾病的临床诊断.     

Analysis of motion tracking in echocardiographic image sequences: Influence of system geometry and point-spread function

This paper focuses on motion tracking in echocardiographic ultrasound images. The difficulty of this task is related to the fact that echographic image formation induces decorrelation between the underlying motion of tissue and the observed speckle motion. Since Meunier’s seminal work, this phenomenon has been investigated in many simulation studies as part of speckle tracking or optical flow-based motion estimation techniques. Most of these studies modeled image formation using a linear convolution approach, where the system point-spread function (PSF) was spatially invariant and the probe geometry was linear. While these assumptions are valid over a small spatial area, they constitute an oversimplification when a complete image is considered. Indeed, echocardiographic acquisition geometry relies on sectorial probes and the system PSF is not perfectly invariant, even if dynamic focusing is performed.This study investigated the influence of sectorial geometry and spatially varying PSF on speckle tracking. This was done by simulating a typical 64 elements, cardiac probe operating at 3.5 MHz frequency, using the simulation software Field II. This simulation first allowed quantification of the decorrelation induced by the system between two images when simple motion such as translation or incompressible deformation was applied. We then quantified the influence of decorrelation on speckle tracking accuracy using a conventional block matching (BM) algorithm and a bilinear deformable block matching (BDBM) algorithm. In echocardiography, motion estimation is usually performed on reconstructed images where the initial sectorial (i.e., polar) data are interpolated on a cartesian grid. We therefore studied the influence of sectorial acquisition geometry, by performing block matching on cartesian and polar data.Simulation results show that decorrelation is spatially variant and depends on the position of the region where motion takes place relative to the probe. Previous studies did not consider translation in their experiments, since their simulation model (spatially invariant PSF and linear probe) yields by definition no decorrelation. On the opposite, our realistic simulation settings (i.e., sectorial probe and realistic beamforming) show that translation yields decorrelation, particularly when translation is large (above 6 mm) and when the moving regions is located close to the probe (distance to probe less than 50 mm).The tracking accuracy study shows that tracking errors are larger for the usual cartesian data, whatever the estimation algorithm, indicating that speckle tracking is more reliable when based on the unconverted polar data: for axial translations in the range 0-10 mm, the maximum error associated to conventional block matching (BM) is 4.2 mm when using cartesian data and 1.8 mm for polar data. The corresponding errors are 1.8 mm (cartesian data) and 0.4 mm (polar data) for an applied deformation in the range 0-10%. We also show that accuracy is improved by using the bilinear deformable block matching (BDBM) algorithm. For translation, the maximum error associated to the bilinear deformable block matching is indeed 3.6 mm (cartesian data) and 1.2 mm (polar data). Regarding deformation, the error is 0.7 mm (cartesian data) and 0.3 mm (polar data). These figures also indicates that the larger improvement brought by the bilinear deformable block matching over standard block matching logically takes place when deformation on cartesian data is considered (the error drops from 1.8 to 0.7 mm is this case).We give a preliminary evaluation of this framework on a cardiac sequence acquired with a Toshiba Powervision 6000 imaging system using a probe operating at 3.25 MHz. As ground truth reference motion is not available in this case, motion estimation performance was evaluated by comparing a reference image (i.e., the first image of the sequence) and the subsequent images after motion compensation has been applied. The comparison was quantified by computing the normalized correlation between the reference and the motion-compensated images. The obtained results are consistent with the simulation data: correlation is smaller for cartesian data, whatever the estimation algorithm. The correlation associated to the conventional block matching (BM) is in the range 0.45-0.02 when using cartesian data and in the range 0.65-0.2 for polar data. The corresponding correlation ranges for the bilinear deformable block matching are 0.98-0.2 and 0.98-0.55. In the same way these figures indicate that the bilinear deformable block matching yield a larger improvement when cartesian data are considered (correlation range increases from 0.45-0.02 to 0.98-0.2 in this case).     

基于多相组重建的航空图像超分辨率算法

为提高航空图像的空间分辨率, 提出一种基于多相组重建的超分辨率算法. 融合图像间的互补信息, 将多帧低分辨率图像作为图像基, 参考帧分解为多相组, 利用差异采样特性构建图像基与参考帧之间的的多相组线性关系重建得到高分辨率图像的多项组, 经图像多相分解逆变换获得融合的高分辨率图像. 根据该融合图像的局部内容和结构信息自适应调整控制核核函数, 应用改进的控制核回归算法去除图像模糊和噪声得到清晰的超分辨率图像. 与传统算法相比, 该算法无需图像配准和迭代过程, 计算效率极大地提高. 实验结果表明, 本文算法能够有效提高航空图像的空间分辨率, 在定量评价指标和主观视觉效果方面都有显著提高.     

A comprehensive comparison between shortest-path HARP refinement,SinMod, and DENSEanalysis processing tools applied to CSPAMM and DENSE images

We addressed comprehensively the performance of Shortest-Path HARP Refinement (SP-HR), SinMod, and DENSEanalysis using 2D slices of synthetic CSPAMM and DENSE images with realistic contrasts obtained from 3D phantoms. The three motion estimation techniques were interrogated under ideal and no-ideal conditions (with MR induced artifacts, noise, and through-plane motion), considering several resolutions and noise levels. Under noisy conditions, and for isotropic pixel sizes of 1.5 mm and 3.0 mm in CSPAMM and DENSE images respectively, the nRMSE obtained for the circumferential and radial strain components were 10.7 ± 10.8% and 25.5 ± 14.8% using SP-HR, 11.9 ± 2.5% and 29.3 ± 6.5% using SinMod, and 6.4 ± 2.0% and 18.2 ± 4.6% using DENSEanalysis. Overall, the results showed that SP-HR tends to fail for large tissue motions, whereas SinMod and DENSEanalysis gave accurate displacement and strain field estimations, being the last which performed the best.     

On noise reduction in strain maps obtained with the grid method by averaging images affected by vibrations

Any image-based contactless measurement system has a limited resolution because of sensor noise. If the sensor is rigorously static with respect to the imaged object, a possibility is to reduce noise by averaging images acquired at different times. This paper discusses images of a pseudo-periodic grid used in experimental solid mechanics to give estimations of in-plane displacement and strain components of a deformed flat specimen. Because of the magnification factor which is employed, the grid images are often affected by residual vibrations, thereby invalidating the assumption that the sensor is static. The averaged grid image is thus a biased estimator of the unknown noise-free image. In spite of this, we prove that the retrieved displacement and strain components still benefit from noise reduction by time-averaging. A theoretical model is discussed, and experiments on real and synthetic data sets are provided.     

运动与离焦模糊图像的复原

在运动和离焦所引起的图像模糊的情况中,本文提出了一种新的基于霍夫变换区分离焦模糊和运动模糊两类模糊的方法.该方法通过比较霍夫变换矩阵中的亮点数来区分两类模糊,不仅正确率达到100%,而且抗干扰性能好;其次通过对运动模糊图像做两次方向微分,估计其模糊方向,提高了模糊方向的估计准确度;最后利用改进的Prewiit算子和费米函数计算模糊图像的刃边函数,进而得到图像的调制传递函数,再利用维纳滤波复原图像.实验结果表明:本文算法不仅具有有效性和强抗噪音能力,而且对图像的信噪比要求可以低到20 dB;与传统算法相比,提高了图像的复原质量.     

Laser speckle decorrelation in NDT

The random noise of the laser speckle field which develops at the focusing plane of an imaging system, is, by now, efficiently used in several interferometric techniques as an information carrier of the macroscopic wavefront distortion induced by the surface displacement field of the object under investigation. The actual noise in this kind of techniques is represented by the speckle decorrelation at the image plane — i.e. the destruction of the carrier — which may be caused by the modification of the texture surface (e.g. by yielding under a severe stress state), but it is inherently produced by the same displacement field under measurement. In the paper the phenomenon of laser speckle decorrelation is numerically simulated and experimentally investigated with the aim of estimating its sensitivity to local deformation and assessing a possible field of application. Satisfactory results in the field of NDT of multilayer fiber-reinforced composites were obtained by reducing the diaphragm of the lens to increase the sensitivity of the imaging system to speckle decorrelation induced by local deformation; unfortunately this simple approach requires a considerable amount of laser power for illuminating the object. Different aperture shapes were therefore numerically simulated which provided improved efficiency and sensitivity and whereby a semi-quantitative analysis of the displacement field could be experimented.     

不同模糊尺度下运动模糊方向的鉴别

为了有效减弱高动态环境对图像采集的干扰,利用模糊图像的频谱特性,提出了一种适合不同模糊尺度的运动模糊方向估计方法。该方法对比不同模糊尺度图像频谱中心亮条纹边缘特征的差别,通过计算其曲率半径实现不同模糊尺度图像的量化鉴别,在确定图像模糊尺度的大小之后,分别利用倒频谱、二次傅氏变换对模糊图像频谱中心亮线特征进行提取,考虑图像高宽比、中心十字亮线的不利影响,在二值化处理的基础上剔除十字亮线,通过亮线特征点直线拟合完成模糊方向估计。实验结果表明,该算法能够有效鉴别不同模糊尺度的运动模糊方向,估计精度较其他同类算法更高,相对误差率均小于0.02。     

Optimal precision of parameter estimation in images with local sub-Poissonian quantum fluctuations

Non-classical quantum effects allow light with local sub-Poissonian fluctuations below shot noise to be produced. We show that using such light can improve the estimation precision of a parameter in an image beyond the standard Poissonian limit. This benefit is theoretically investigated by means of a phenomenological model of local sub-Poissonian noise which assumes the independence of the fluctuations in each pixel. In particular, a bound on the best precision expectable independently of the exact unbiased estimation protocol used, which is given by the Cramer-Rao bound, is determined from this model. The numerical simulations presented in the special case of the estimation of a displacement of an image perturbed with local sub-Poissonian noise show that a standard estimator can overcome the classical Poissonian limit by reaching this limit precision only beyond a certain value of the photon flux which we characterize. We eventually present some numerical results that demonstrate the generality of the model proposed, of the optimality bounds and of the estimator performance.     

Correlation analysis of the beam angle dependence for elastography

Signal decorrelation is a major source of error in the displacements estimated using correlation techniques for elastographic imaging. Previous papers have addressed the variation in the correlation coefficient as a function of the applied compression for a finite window size and an insonification angle of zero degrees. The recent use of angular beam-steered radio-frequency echo signals for spatial angular compounding and shear strain estimation have demonstrated the need for understanding signal decorrelation artifacts for data acquired at different beam angles. In this paper, we provide both numerical and closed form theoretical solutions of the correlation between pre- and post-compression radio-frequency echo signals acquired at a specified beam angle. The expression for the correlation coefficient obtained is a function of the beam angle and the applied compression for a finite duration window. Accuracy of the theoretical results is verified using tissue-mimicking phantom experiments on a uniformly elastic phantom using beam-steered data acquisitions on a linear array transducer. The theory predicts a faster decorrelation with changes in the beam or insonification angle for longer radio-frequency echo signal segments and at deeper locations in the medium. Theoretical results provide useful information for improving angular compounding and shear strain estimation techniques for elastography.     

The combined effect of nonlinear filtration and window size on the accuracy of tissue displacement estimation using detected echo signals

In cardiac elastography, the regional strain and strain rate imaging is based on displacement estimation of tissue sections within the heart muscle carried out with various block-matching techniques (cross-correlation, sum of absolute differences, sum of squared differences, etc.). The accuracy of these techniques depends on a combination of ultrasonic imaging parameters such as ultrasonic frequency of interrogation, signal-to-noise ratio, size of a kernel used in a block-matching algorithm, type of data and speckle decorrelation. In this paper, we discuss the possibility to enhance the accuracy of the displacement estimation via nonlinear filtering of B-mode images before block-matching operation. The combined effect of a filter algorithm and a kernel size on the accuracy of the displacement estimation is analyzed using a 36-frame sequence of grayscale B-mode images of a human heart acquired by an ultrasound system operating at 1.77 MHz. It is shown that the nonlinear filtering of images enables to obtain the desired accuracy (less than one pixel) of the displacement estimation with smaller kernels than without filtering. These results are obtained for two filters--an adaptive anisotropic diffusion filter and a nonlinear Gaussian filter chain.     

小模糊尺度下运动模糊方向鉴别算法研究

针对现有模糊方向鉴别算法检测小尺度运动模糊图像存在误差的问题,基于运动模糊图像二次傅里叶变换后的频谱特性,分析了其误差成因,并提出了一种适用于小尺度运动模糊图像模糊方向鉴别的新算法。首先对小尺度运动模糊图像的频谱进行细化,通过中值滤波对细化图像去噪,避开了频谱噪声带来的估计误差问题;其次,选取灰度中值作为阈值进行二值化,同时去除二值图像的中心十字亮线和中心亮斑,使模糊方向特征更加明显;然后用投影变换计算出亮条纹方向得到小尺度模糊图像的方向估计。最后通过仿真验证了算法在运动模糊尺度为3～10像素的小尺度情况下的实效性。实验结果表明,该算法相比其他同类算法对于小尺度运动模糊图像的模糊方向估计精度更高。