超声平面波同相正交信号频域波束形成算法

针对频域平面波波束形成算法尚不能直接应用于采用正交解调的超声成像系统中的实际问题,提出一种平面波同相正交信号频域波束形成方法。以平面波射频信号频域波束形成算法为基础,根据射频信号与同相正交信号波数空间变量之间的关系,推导了平面波同相正交信号与对应图像的频谱映射表达式,从而实现对正交解调后信号的频域超声图像重建。采用2016年Plane Wave Imaging Challenge in Medical Ultrasound (PICMUS)发布的仿真、仿体及在体原始回波数据对这一方法进行验证,并评估图像的分辨率和对比噪声比。仿真和仿体实验结果表明,相对于射频信号的频域波束形成算法,该算法可获得与之相同的图像质量,并将成像速度提高了约4倍。在体实验数据的成像结果也验证了该算法在实际应用中的有效性。      

超声平面波同相正交信号频域波束形成算法

针对频域平面波波束形成算法尚不能直接应用于采用正交解调的超声成像系统中的实际问题,提出一种平面波同相正交信号频域波束形成方法。以平面波射频信号频域波束形成算法为基础,根据射频信号与同相正交信号波数空间变量之间的关系,推导了平面波同相正交信号与对应图像的频谱映射表达式,从而实现对正交解调后信号的频域超声图像重建。采用2016年Plane Wave Imaging Challenge in Medical Ultrasound (PICMUS)发布的仿真、仿体及在体原始回波数据对这一方法进行验证,并评估图像的分辨率和对比噪声比。仿真和仿体实验结果表明,相对于射频信号的频域波束形成算法,该算法可获得与之相同的图像质量,并将成像速度提高了约4倍。在体实验数据的成像结果也验证了该算法在实际应用中的有效性。     

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。     

基于液晶可调滤光器的多光谱图像色彩复制装置的设计与实现

基于新型的多维成像技术,研制了一种基于液晶可调滤光器(Liquid Crystal Tunal Filter,LCTF)的多光谱图像色彩复制装置,实现了对图像色彩信号的复制,将多光谱成像技术应用于色彩复制领域。描述了系统的工作原理、装置的详细设计与实现过程等,通过该装置对计量院校准过的标准色卡复制成像,获取了31个通道多光谱图像,色差ΔE_(Lab)=2.7,合成后的彩色图像质量良好,色差小、复制精度高,可用于多个领域图像色彩的精确复制和可视化逼真再现。     

无造影剂增强的超快超声脊髓微血管成像方法

微小血管及其血流实时成像对监测生物体血氧代谢等具有重要意义.在无微泡造影剂的情况下,传统超声多普勒技术仍较难实现高信噪比的微小血管成像.本研究提出了一种无造影剂增强的超快超声脊髓微血管成像方法.本研究从基于多角度复合平面波的高帧频成像技术出发,提出基于特征值分解的频率-幅值双阈值滤波法,从而将脊髓组织信号和微血流信号分离,可实现脊髓内微血流的动态成像.在体成像实验结果表明,无超声造影剂时,超快超声多普勒成像技术仍可获得较为清晰的大鼠脊髓内微血流的实时图像,并能够清晰地呈现脊髓受损所致的微血流缺失状况.定量分析结果表明,增大复合平面波角度数可有效提高图像的信噪比.综上,超快超声多普勒成像技术有潜力被应用于脊髓内微血管成像及功能实时监测与动态评价,相关结果可为脊髓功能成像方法的研究提供借鉴.     

基于RCA阵列三维超快超声血流成像方法仿真研究

三维超快成像是超声技术发展的重要方向.基于二维全采样阵列的传统三维成像方法需要较多成像阵元和采样通道,其紧密的阵元排列设计也客观上限制了阵列孔径大小和成像分辨率.行列寻址(row-column addressing, RCA)探头以行列检索的方式将通道数自N×N减少为N+N,从而极大地降低了阵列的硬件实现成本.本文仿真了中心频率为6MHz的128行+128列的RCA阵列,结合多角度平面波正交复合成像方法,通过延时叠加(delay and sum, DAS)波束合成、基于特征值分解(singular value decomposition, SVD)的杂波滤除和自相关多普勒速度求解算法,实现了血流仿体的多普勒成像,并分析了不同复合角度序列对成像效果的影响.定量分析表明,当角度数从5个增至33个时,–6 dB分辨率从0.986 mm提升至0.493 mm;当复合角度为17个时,功率多普勒图像的SNR可达30 dB,彩色多普勒沿直径方向的速度分布和真实值的平均误差约为26.0%.以上结果表明,基于RCA阵列的三维成像技术能够获得三维B-mode、功率多普勒和彩色多普勒图像,增大复合平面波角度...     

多帧迭代盲解卷积在激光反射断层成像的应用

激光反射断层成像是一种新型的远距离高分辨率成像手段。反射回波可以近似视作发射脉冲和目标反射系数投影分布的加噪卷积,因此发射脉冲的展宽将显著影响重建图像的分辨率。现有的滤波反投影方法不能有效解决这个问题,而脉冲压缩和解卷积可以从回波中还原目标反射率分布投影,进而提高重建图像质量。基于多角度测量的相似性,提出了一种多帧迭代盲解卷积逼近方法,对一维回波信号进行解卷积,并在实际激光雷达上进行了实验,重建结果表明,此算法能显著提高成像的分辨率和细节,并能对发射脉冲给出参考。     

基于CCD电极直接驱动控制的双脉冲发光图像高速曝光技术原理研究

电荷耦合器件(CCD)是一类高性能的光电成像器件,具有成像阵列大、图像质量好的特点。但由于正常工作驱动时序复杂,工作帧频一般较低,无法满足较高成像帧频的要求。针对一种双脉冲发光图像的高速高分辨高质量成像要求,根据CCD信号电荷收集及转移的电极驱动特性,选择合适的CCD类型,以电荷转移时序为时间分隔界限,设计了一种电极直接进行控制的时序,实现了两个光脉冲图像的分离积分及信号转移、读出等,完成了双脉冲发光图像的等效高帧频曝光的原理验证,在保持CCD原有高成像质量的情况下获得了μs级间隔的两幅图像可分辨的能力,并实现了一种二分幅相机系统。     

基于调频信号发射的超声造影剂谐波成像方法

提出了一种能够提取超声造影剂回波中二次谐波的非线性成像方法,从数学原理、仿真计算和声学实验三个方面对造影剂血流灌注成像方法进行了研究。首次将调频信号发射技术用于医学超声造影剂谐波成像领域,仿真计算和声学实验结果表明:为了获得较好的图像质量,发射调频信号应该具有合适的包络;发射信号带宽与解码匹配滤波器带宽之间必须有一个带宽间隔;适当降低发射声压能够降低生物组织的谐波。应用编码发射方法和解码滤波器,得到了造影剂二次谐波图像,此图像具有较好的信号噪声比和造影剂组织比。声学实验结果和理论计算结果完全吻合。     

基于超快超声多普勒的三维脑损伤成像方法研究

三维超声微血管成像可直观呈现血流信息,对于脑血管疾病诊断和治疗具有重要意义。本文旨在将超快超声成像技术、超快超声功率多普勒技术和机械扫描相结合,实现脑血管三维成像和脑缺血区域评价。通过工程实现,完成了可同步控制微型线性位移平台移动和超声阵列超快发射、高速采集与压缩存储的三维扫描数据采集序列与系统。利用GPU并行运算,高效实现了超声图像波束合成方法,对原始射频超声数据完成重建。进而,基于SVD杂波滤除技术,从重建三维超声数据中提取了脑部的动态小血管信号,并获得了各切面的功率多普勒成像和冠状面彩色多普勒超声小血管成像。最后,采用体素方法对三维脑血管进行重建。大鼠在体实验结果表明,该成像系统可用于三维脑血管网络在体成像,以及脑血管损伤区域定位与量化评价。本工作对脑病检测技术发展与诊断方法研究具有一定的借鉴意义。此外,相关检测系统和成像算法具有一定普适性,对其他富含微血流血管的组织检测也有一定的参考价值。     

Acoustic analysis by spherical microphone array processing of room impulse responses

Spherical microphone arrays have been recently used for room acoustics analysis, to detect the direction-of-arrival of early room reflections, and compute directional room impulse responses and other spatial room acoustics parameters. Previous works presented methods for room acoustics analysis using spherical arrays that are based on beamforming, e.g., delay-and-sum, regular beamforming, and Dolph-Chebyshev beamforming. Although beamforming methods provide useful directional selectivity, optimal array processing methods can provide enhanced performance. However, these algorithms require an array cross-spectrum matrix with a full rank, while array data based on room impulse responses may not satisfy this condition due to the single frame data. This paper presents a smoothing technique for the cross-spectrum matrix in the frequency domain, designed for spherical microphone arrays, that can solve the problem of low rank when using room impulse response data, therefore facilitating the use of optimal array processing methods. Frequency smoothing is shown to be performed effectively using spherical arrays, due to the decoupling of frequency and angular components in the spherical harmonics domain. Experimental study with data measured in a real auditorium illustrates the performance of optimal array processing methods such as MUSIC and MVDR compared to beamforming.     

A high-speed image sensing technique with adjustable frame rate based on an ordinary CCD

In the sinusoidal phase modulating interferometer technique, the high-speed CCD is necessary to detect the interference signals. The reason of ordinary CCD's low frame rate was analyzed, and a novel high-speed image sensing technique with adjustable frame rate based on an ordinary CCD was proposed. And the principle of the image sensor was analyzed. When the maximum frequency and channel bandwidth were constant, a custom high-speed sensor was designed by using the ordinary CCD under the control of the special driving circuit. The frame rate of the ordinary CCD has been enhanced by controlling the number of pixels of every frame; therefore, the ordinary of CCD can be used as the high frame rate image sensor with small amount of pixels. The multi-output high-speed image sensor has the deficiencies of low accuracy, and high cost, while the high-speed image senor with small number of pixels by using this technique can overcome theses faults. The light intensity varying with time was measured by using the image sensor. The frame rate was up to 1600 frame per second (f/s), and the size of every frame and the frame rate were adjustable. The correlation coefficient between the measurement result and the standard values were higher than 0.98026, and the relative error was lower than 0.53%. The experimental results show that this sensor is fit to the measurements of sinusoidal phase modulating interferometer technique.     

Adaptive beamforming for photoacoustic imaging

An adaptive photoacoustic image reconstruction technique that combines coherence factor (CF) weighting and the minimum variance (MV) method is introduced. The backprojection method is widely used to reconstruct photoacoustic tomography images. Owing to the scattering of light, the quality of the photoacoustic imaging can be degraded. CF, an adaptive weighting technique, is known to improve the lateral resolution of photoacoustic images. In addition, an MV adaptive beamforming method can further improve the image quality by suppressing signals from off-axis directions. Experimental studies are performed to quantify the spatial resolution and contrast of the adaptive photoacoustic beamforming methods.     

Single frame blind image deconvolution by non-negative sparse matrix factorization

Novel approach to single frame multichannel blind image deconvolution has been formulated recently as non-negative matrix factorization problem with sparseness constraints imposed on the unknown mixing vector that accounts for the case of non-sparse source image. Unlike most of the blind image deconvolution algorithms, the novel approach assumed no a priori knowledge about the blurring kernel and original image. Our contributions in this paper are: (i) we have formulated generalized non-negative matrix factorization approach to blind image deconvolution with sparseness constraints imposed on either unknown mixing vector or unknown source image; (ii) the criteria are established to distinguish whether unknown source image was sparse or not as well as to estimate appropriate sparseness constraint from degraded image itself, thus making the proposed approach completely unsupervised; (iii) an extensive experimental performance evaluation of the non-negative matrix factorization algorithm is presented on the images degraded by the blur caused by the photon sieve, out-of-focus blur with sparse and non-sparse images and blur caused by atmospheric turbulence. The algorithm is compared with the state-of-the-art single frame blind image deconvolution algorithms such as blind Richardson-Lucy algorithm and single frame multichannel independent component analysis based algorithm and non-blind image restoration algorithms such as multiplicative algebraic restoration technique and Van-Cittert algorithms. It has been experimentally demonstrated that proposed algorithm outperforms mentioned non-blind and blind image deconvolution methods.     

Adaptive field-of-view imaging for efficient receive beamforming in medical ultrasound imaging systems

Quadrature demodulation-based phase rotation beamforming (QD-PRBF) is commonly used to support dynamic receive focusing in medical ultrasound systems. However, it is computationally demanding since it requires two demodulation filters for each receive channel. To reduce the computational requirements of QD-PRBF, we have previously developed two-stage demodulation (TSD), which reduces the number of lowpass filters by performing demodulation filtering on summation signals. However, it suffers from image quality degradation due to aliasing at lower beamforming frequencies. To improve the performance of TSD-PRBF with reduced number of beamforming points, we propose a new adaptive field-of-view (AFOV) imaging method. In AFOV imaging, the beamforming frequency is adjusted depending on displayed FOV size and the center frequency of received signals. To study its impact on image quality, simulation was conducted using Field II, phantom data were acquired from a commercial ultrasound machine, and the image quality was quantified using spatial (i.e., axial and lateral) and contrast resolution. The developed beamformer (i.e., TSD-AFOV-PRBF) with 1024 beamforming points provided comparable image resolution to QD-PRBF for typical FOV sizes (e.g., 4.6% and 1.3% degradation in contrast resolution for 160 mm and 112 mm, respectively for a 3.5 MHz transducer). Furthermore, it reduced the number of operations by 86.8% compared to QD-PRBF. These results indicate that the developed TSD-AFOV-PRBF can lower the computational requirement for receive beamforming without significant image quality degradation.     

基于方向金字塔框架变换的遥感图像融合算法

为了综合利用多光谱遥感图像与全色遥感图像之间的互补信息,提出了一种方向金字塔框架变换(SPFT),并基于此变换提出了一种遥感图像融合算法。具体融合过程是将多光谱图像的每个波段分别与高分辨力全色图像进行融合,首先将高分辨力全色图像与多光谱图像的待融合波段进行直方图匹配,然后对该波段图像以及直方图匹配后的高分辨力全色图像分别进行方向金字塔框架变换分解,融合过程就是对两图像方向金字塔框架变换分解后的系数进行组合,最后对组合后的系数进行方向金字塔框架逆变换即可得到该波段图像与高分辨力全色图像的融合图像。实验结果表明该算法在性能上优于基于亮度-色调-饱和度(1HS)的彩色空间变换以及基于离散小波框架变换(DWFT)的遥感图像融合方法,尤其对源图像之间存在配准误差的情况。     

基于FPGA的近红外实时透雾成像方法

针对雾天图像的退化现象,提出采用近红外波段成像和视频图像处理技术相结合的透雾成像方法。根据视频图像相邻两场直方图相似性特点,提出了改进的直方图均衡化算法处理雾天降质图像。改进算法简化系统结构,降低逻辑设计复杂度,节约了高速存储器部分硬件资源。算法经过MATLAB仿真验证,并在FPGA视频图像处理平台上硬件实现。实验证明改进算法增强雾天图像的同时满足标准视频图像处理25帧/秒的实时性要求,结合近红外波段透雾能力使雾天能见距离提高1.5倍以上。     

基于压缩感知的矢量阵聚焦定位方法

本文针对噪声源近场定位识别问题,利用声源分布在空间域具有稀疏性,在压缩感知理论框架下建立了新体系下的矢量阵聚焦波束形成方法,用于解决同频相干声源的定位识别问题.新方法可在小快拍下准确获得噪声源的空间位置,且不损失对噪声源贡献相对大小的评价能力.通过详细的理论推导、仿真分析和试验验证,证明了基于压缩感知的矢量阵聚焦定位新方法本质上实现了l1范数正则化求解下的波形恢复和空间谱估计,因此具有较高的定位精度,较强的相干声源分辨能力、准确的声源贡献相对大小评价能力以及较高的背景压制能力,可应用于水下复杂噪声源的定位识别.     

A novel frame shift and integral technique for processing low-light-level moving image sequence

A new method for processing low-light-level moving image sequence is proposed, in which (1) a novel algorithm based on difference processing has been firstly developed to determine the motion parameters of moving image sequence, (2) the spatial relativity of the frames within moving image sequence can be then well established after frame shifting according to motion parameters obtained above, (3) finally, frame integration method can be applied to each processed frame, thereby increasing the signal-to-noise ratio of low-light-level moving image sequence. Experiments have been carried out to verify the validity of the proposed method, which show that the parameters obtained by the developed algorithm coincide well with the actual values, and the SNRs of the moving image sequences were effectively increased with the proposed method, indicating that the method offers significant advantages in the enhancement of low-light-level moving image sequence.