一种广义旁瓣相消的超声成像算法

针对最小方差和相干系数结合算法在超声成像对比度、分辨率和对噪声的鲁棒性方面存在的不足, 提出一种广义旁瓣相消的成像算法. 首先基于最小方差准则, 构造广义旁瓣相消器, 获得自适应与非自适应两部分加权向量, 然后根据接收信号的协方差矩阵构建特征阈值信号子空间, 并将获得的加权向量投影到此特征信号子空间的左奇异矢量空间中, 获得新的加权矢量. 通过Field II点目标和吸声斑仿真结果表明: 该方法获得的超声图像在对比度、分辨率和对噪声的鲁棒性上均优于传统延时叠加算法及最小方差和相干系数结合算法, 同时将广义旁瓣相消算法获得的加权向量与符号相干系数结合, 还能进一步提高超声图像质量. 最后通过geabr_0实验数据进行测试, 结果表明: 提出算法的分辨率和对比度及对噪声的鲁棒性上均优于传统延时叠加算法及最小方差和相干系数结合算法.     

信噪比后滤波与特征空间融合的最小方差超声成像算法

为了提高超声成像空间分辨率和对比度,提出了一种信噪比后滤波与特征空间融合的最小方差波束形成算法。首先,利用信号子空间划分将最小方差算法得到的权矢量投影到信号子空间中提高成像对比度,然后基于信号相干性设计滤波系数,并引入基于信噪比的噪声加权系数,最终得到融合信噪比后滤波与特征空间的最小方差算法。为验证本算法的有效性,使用FieldⅡ对点目标和吸声斑目标进行了仿真实验验证,并采用密歇根大学geabr_0实验数据进行成像。实验结果表明:所提算法在对比度和分辨率上均有所提高,明显优于传统延时叠加算法,最小方差算法和ESBMV_wiener算法,且对噪声具有较强鲁棒性。      

特征空间和符号相干系数融合的最小方差超声波束形成

为了提高医学超声成像的空间分辨率,提出一种融合了特征空间最小方差与符号相干系数的波束形成方法。首先利用最小方差法计算回波数据的协方差矩阵和加权向量;然后对协方差矩阵进行特征分解得到信号子空间,并将加权向量投影到该空间上;最后计算符号相干系数,用于优化特征空间法得到的回波信号,最终获得超声成像数据。为验证算法的有效性,对医学超声成像中常用的点目标、斑目标进行仿真,对点目标仿体和人体颈动脉组织进行超声成像实验。结果表明:所提出的方法在分辨率、对比度以及稳健性等方面都优于传统的延时叠加算法、最小方差算法、特征空间最小方差法以及特征空间与相干系数融合的方法。     

特征空间和符号相干系数融合的最小方差超声波束形成

为了提高医学超声成像的空间分辨率,提出一种融合了特征空间最小方差与符号相干系数的波束形成方法。首先利用最小方差法计算回波数据的协方差矩阵和加权向量;然后对协方差矩阵进行特征分解得到信号子空间,并将加权向量投影到该空间上;最后计算符号相干系数,用于优化特征空间法得到的回波信号,最终获得超声成像数据。为验证算法的有效性,对医学超声成像中常用的点目标、斑目标进行仿真,对点目标仿体和人体颈动脉组织进行超声成像实验。结果表明:所提出的方法在分辨率、对比度以及稳健性等方面都优于传统的延时叠加算法、最小方差算法、特征空间最小方差法以及特征空间与相干系数融合的方法。      

特征空间最小方差波束形成与相关系数特征值加权相融合的超声成像算法

为了进一步提高超声成像的质量,提出一种信号特征空间的最小方差波束形成与相关系数特征值加权相融合的超声成像算法。利用超声回波信号具有一定的相关性,而相关系数空间最大特征值可以反映回波信号相关性较强的性质,将该特征值作为自适应加权系数对信号特征空间最小方差波束形成(EIBMV)的结果进行加权成像,得到高质量的成像结果。通过对散射点目标和斑目标的Field II仿真,结果表明该算法相对于EIBMV算法,亮斑对比度提高了4.22 dB,暗斑对比度提高了1.88 dB,并且进一步提高了横向分辨率。      

超声成像中基于特征空间的前后向最小方差波束形成

针对最小方差(MV)波束形成在算法稳健性和超声成像对比度方面存在的缺点,提出一种将特征空间法和前后向空间平滑法融合用于最小方差波束形成的超声成像方法。首先用前后向空间平滑取代传统的前向空间平滑,得到更精确的协方差矩阵;然后计算最优加权向量,并将该向量投影到由协方差矩阵特征空间构造的信号子空间中;最后利用投影所获得的向量与阵元数据进行运算得到成像回波数据。为了验证算法的有效性,对医学成像中常用的点目标和斑目标进行了成像实验。仿真结果表明:所提出的方法不依赖于对角加载参数的选取,在保持MV算法高分辨率的同时,还有效提高图像的对比度和算法的稳健性。      

互相关自适应加权的医学超声成像算法研究

根据超声成像系统的超声回波信号互相关性,提出互相关自适应加权超声成像算法.该算法根据散射点回波信号之间的空间相关性设置加权系数,对不同位置的散射点进行自适应加权成像,从而降低了成像系统的旁瓣,抑制了相关性较差的噪声.通过Field II仿真的点目标和吸声斑目标处理结果表明该方法成像的横向和纵向分辨率高,成像速度快.相对于延时叠加(DAS)算法,该算法对散射点成像可提高对比度16 dB,对于吸声斑成像可提高对比度0.85 dB.最后采用完备数据集进行实验,结果表明该算法成像分辨率优于DAS算法,对比度提高了17 dB.     

非线性合成孔径聚焦超声成像

论文介绍了合成孔径聚焦超声成像系统原理。建立了一个无损检测超声成像系统。同时，为了进一步提高分辨率，设计了基于相关系数的非线性合成孔径聚焦算法。然后利用此算法对试块成像，结果表明，与延时叠加合成孔径算法相比，基于相关性分析的非线性合成孔径算法提高了图像的分辨率，改善了图像质量。     

一种机载合成孔径成像激光雷达聚束模式成像算法

合成孔径成像激光雷达是一种新的主动式有源的成像系统,可以获得比合成孔径雷达更高的分辨率,和更接近光学图片的效果.首先,在理想条件下分析了调频连续波的信号模型,推导出在连续波系统聚束模式下一种适用于机载合成孔径成像激光雷达系统的频率变标算法.然后,使用傅里叶变换法对符合von Karman谱的随机相位屏模拟大气湍流,并分析了Fried参量和合成孔径长度之间的关系.最后,仿真说明真空中采用方位预处理可以消除图像重影,并且补偿多普勒频移项可以消除8.6～9.3dB的能量损失和使图像散焦的现象.而在有大气影响时,合成孔径长度的选择小于Fried参量时,图像方位向可以良好聚焦.     

结合空化微泡母小波变换的高空化噪声比超快速 主动空化成像方法*

本文提出一种结合空化微泡母小波技术(Cavitation Bubble Wavelet Transform, CBWT)、波束合成和平方差值求和减影(Sum-of-Squared Differences, SSD)的超快速主动空化成像方法。该方法首先发射平面波并接收空化回波信号；其次,基于RPNNP模型构建空化微泡母小波,对空化回波信号进行连续小波变换；再次,对获得的小波系数进行波束合成,包括延迟叠加算法(Delay-and-Sum, DAS)、最小方差算法(Minimum-Variance, MV)和相干系数最小方差算法(Coherence-Factor-based-Minimum-Variance, MVCF),再结合SSD,得到空化图像。结果表明,与未采用CBWT相比,基于CBWT-DAS-SSD、CBWT-MV-SSD和CBWT-MVCF-SSD的空化噪声比分别提高了16.34 dB、15.07 dB、17.71 dB。本文方法可提高空化成像质量,为空化动态实时监控提供参考。     

Medical ultrasound imaging method combining minimum variance beamforming and general coherence factor

In medical ultrasound imaging field,in order to obtain high resolution and correct the phase errors induced by the velocity in-homogeneity of the tissue,a high-resolution medical ultrasound imaging method combining minimum variance beamforming and general coherence factor was presented.First,the data from the elements is delayed for focusing;then the multi-channel data is used for minimum variance beamforming;at the same time,the data is transformed from array space to beam space to calculate the general coherence factor;in the end, the general coherence factor is used to weight the results of minimum variance beamforming. The medical images are gotten by the imaging system.Experiments based on point object and anechoic cyst object are used to verify the proposed method.The results show the proposed method in the aspects of resolution,contrast and robustness is better than minimum variance beamforming and conventional beamforming.     

Optimum beamformer in correlated source environments

A new method for overcoming signal cancellation problems due to correlated interferences which occur in a minimum variance distortionless response beamformer is proposed. Instead of decorrelating the correlated interferences, the coherently combining signal-to-interference plus noise ratio (CC-SINR) beamformer regards them as replicas of the desired signal and coherently combines them with the desired signal. This method uses an eigenvector constraint that suppresses only noise and uncorrelated interferences but retains the desired signal and correlated interferences. The CC-SINR beamformer does not require any preliminary information on correlated interferences. The signal-to-interference plus noise ratio (SINR) of the proposed beamformer output was compared to that of a conventional SINR beamformer when correlated interference, uncorrelated interference, and white noise exist. In addition, various key parameters that affect the performance of the beamformer, such as signal-to-noise ratio, uncorrelated interference-to-noise ratio, angular separation between signals, attenuation factor, phase delay of correlated interference, and the number of sensors were analyzed. All of the experimental results were in good agreement with the analytical results.     

Eigenspace-based minimum variance beamformer combined with Wiener postfilter for medical ultrasound imaging

In this paper, a new beamformer which combines the eigenspace-based minimum variance (ESBMV) beamformer with the Wiener postfilter is proposed for medical ultrasound imaging. The primary goal of this work is to further improve the medical ultrasound imaging quality on the basis of the ESBMV beamformer. In this method, we optimize the ESBMV weights with a Wiener postfilter. With the optimization of the Wiener postfilter, the output power of the new beamformer becomes closer to the actual signal power at the imaging point than the ESBMV beamformer. Different from the ordinary Wiener postfilter, the output signal and noise power needed in calculating the Wiener postfilter are estimated respectively by the orthogonal signal subspace and noise subspace constructed from the eigenstructure of the sample covariance matrix.We demonstrate the performance of the new beamformer when resolving point scatterers and cyst phantom using both simulated data and experimental data and compare it with the delay-and-sum (DAS), the minimum variance (MV) and the ESBMV beamformer. We use the full width at half maximum (FWHM) and the peak-side-lobe level (PSL) to quantify the performance of imaging resolution and the contrast ratio (CR) to quantify the performance of imaging contrast. The FWHM of the new beamformer is only 15%, 50% and 50% of those of the DAS, MV and ESBMV beamformer, while the PSL is 127.2 dB, 115 dB and 60 dB lower. What is more, an improvement of 239.8%, 232.5% and 32.9% in CR using simulated data and an improvement of 814%, 1410.7% and 86.7% in CR using experimental data are achieved compared to the DAS, MV and ESBMV beamformer respectively. In addition, the effect of the sound speed error is investigated by artificially overestimating the speed used in calculating the propagation delay and the results show that the new beamformer provides better robustness against the sound speed errors. Therefore, the proposed beamformer offers a better performance than the DAS, MV and ESBMV beamformer, showing its potential in medical ultrasound imaging.     

Adaptive microphone array for unknown desired speaker's transfer function

The main drawback of minimum variance distortionless response (MVDR) beamformer is the cancellation of the desired speech signal and its degradation in multi-path wave propagation environment. To make the adaptive algorithm robust against room reverberation and to prevent desired signal cancellation an estimation of unknown desired speaker's transfer function was proposed. The estimation is based on the signal and the interference covariance matrices. The estimated transfer function is then applied to the MVDR beamformer. The proposed algorithm was tested on a simulated room with reverberation. The results showed better quality of the restored speech compared to some typical adaptive algorithms.     

Combined Sign Coherent Factor and Delay Multiply and Sum Beamformer for Plane Wave Imaging

Plane wave imaging is a relatively new technique in ultrasound imaging. However, in traditional methods, the coherent information of different emissions and different elements are not considered. In fact, the sign coherent factor (SCF) can improve the lateral resolution of the imaging greatly. In addition, the delay multiply and sum (DMAS) beamformer is mainly based on the spatial correlation of background scattering signals, it has higher contrast and resolution, but suffers from energy loss at great depths. In this paper, combining the advantages of SCF and DMAS, the sign coherent factor delay multiply and sum (SCF-DMAS) beamformer for plane wave imaging is proposed. Unlike the traditional plane wave imaging, the proposed SCF-DMAS beamformer is based on the 2-D echo data set, which improves the imaging speed greatly. Finally, we simulated the point targets and the cyst phantom to evaluate the performance of proposed method. Compared with the traditional plane wave imaging, the lateral resolution of SCF-DMAS beamformer improves greatly for the point targets, and for the cyst phantom the contrast ratio (CR) and contrast-to-noise ratio (CNR) increased by 96.97 and by 79.98% respectively without reducing the frame rate.     

Experimental study of inspection on a metal plate with defect using ultrasound lock-in thermographic technique

The ultrasound lock-in thermographic technique was developed to detect interfacial defects and cracks in a metal plate. Discrete correlation method (DCM), Fourier transformation method (FTM), Short Time Fourier transformation (STF) and Discrete Wavelet Transformation (DWT) algorithms were used to extract the characteristic information of the thermal wave signal generated by ultrasonic wave modulated. It is found that STF and DWT algorithms are available for analyzing the thermal wave signal generated by ultrasonic wave modulated due to higher signal–noise ratio. Experiments were performed to investigate the effect on the amplitude contrast and phase angle contrast by the ultrasound transducer position, initial sonotrode action force and modulation frequency, respectively. Experimental results show that transducer position closed to the defect, higher initial sonotrode action force loaded and optimal modulation frequency selected are help to detect the defects of metal plate using ultrasound lock-in thermographic technique.