Interactive visual analysis of contrast-enhanced ultrasound data based on small neighborhood statistics

Contrast-enhanced ultrasound (CEUS) has recently become an important technology for lesion detection and characterization in cancer diagnosis. CEUS is used to investigate the perfusion kinetics in tissue over time, which relates to tissue vascularization. In this paper we present a pipeline that enables interactive visual exploration and semi-automatic segmentation and classification of CEUS data.For the visual analysis of this challenging data, with characteristic noise patterns and residual movements, we propose a robust method to derive expressive enhancement measures from small spatio-temporal neighborhoods. We use this information in a staged visual analysis pipeline that leads from a more local investigation to global results such as the delineation of anatomic regions according to their perfusion properties. To make the visual exploration interactive, we have developed an accelerated framework based on the OpenCL library, that exploits modern many-cores hardware. Using our application, we were able to analyze datasets from CEUS liver examinations, being able to identify several focal liver lesions, segment and analyze them quickly and precisely, and eventually characterize them.     

Simultaneous speckle reduction and contrast enhancement for ultrasound images: Wavelet versus Laplacian pyramid

Speckle can be described as random multiplicative noise. It hampers the perception and extraction of fine details in the image. Speckle reduction techniques are applied to ultrasound images in order to reduce the noise level and improve the visual quality for better diagnoses. It is also used as preliminary treatment before segmentation and classification. Several methods have been proposed for speckle reduction in ultrasound images. Multiscale contrast enhancement has proven to be very efficient for x-ray images. A recent study by Dippel et al. doing a comparison, contrast enhancement of radiographs (x-ray and mammography), between the Laplacian pyramid and the wavelet one proves that the Laplacian pyramid method gives a better result than the wavelet one; the filtering aspect was not taken into account. In ultrasound images a strong contrast variation exists which is different from x-ray and mammography. In this paper a wavelet pyramid with simultaneous speckle reduction and contrast enhancement was applied for the first time on ultrasound images with the area of interest and compared to a Laplacian enhancement pyramid. The optimum choice of wavelet bases for ultrasound images is investigated in this study. In order to realize a fair comparison, the same nonlinear modification in both multiscale schemes is used. The comparison proves that the wavelet pyramid gives a much better result than the Laplacian one for simultaneous speckle reduction and contrast enhancement of ultrasound images. The text was submitted by the author in English. Ali Samir Saad, 1964. 1996 PhD in image processing, Polytechnics School of the Engineering University of Nantes, France. 1993 Masters in Electronics. 1990 Masters in Digital Image Processing, Institute of Computer Sciences and Communication University of Rennes, France. 1989 BS in Electrical Engineering, University of Saint-Etienne. Academy of Lyon, France. 1996–2000 Research associate at the National Center for Macromolecular Imaging. Baylor, Houston, Texas. Assistant professor at King Saud University, Dept. of Biomedical Technology. Area of research in medical image processing and analysis, 23 publications, member of the American Association for the Advancement of Sciences. Marquis Who’s Who in the World; Cambridge Blue Book 2006.     

超声协同Fenton法与类Fenton法预处理莠去津农药废水研究

针对莠去津农药废水有机物浓度高、含盐量高、有机物难降解等问题,提出了辅以超声协同的Fenton和类Fenton技术进行废水的预处理研究。分别研究了中性条件和酸性条件下,超声协同的Fenton以及类Fenton技术对废水有机物的去除率,并对比单独超声、Fenton以及类Fenton技术。结果表明:辅以超声作用后,TOC去除效果优于单独Fenton和类Fenton技术;针对超声Fenton和超声类Fenton协同技术,相比于中性条件下,酸性条件下能得到更高的TOC去除率,并且超声Fenton技术优于超声类Fenton技术,最高TOC去除率达到48.5%。因此,酸性条件下的超声辅助的芬顿法可作为莠去津农药废水的预处理方法。     

超声辅助离子热合成FeAPO-11分子筛

以1-甲基-3-乙基咪唑溴盐离子液体([emim]Br)为反应介质,采用离子热合成方法合成掺杂过渡金属铁的FeAPO-11分子筛。在合成过程中对FeAPO-11分子筛晶化原液进行超声辐照处理,研究了超声对FeAPO-11分子筛合成过程的影响。采用X射线衍射(XRD)和扫描电镜(SEM)对分子筛样品进行了表征。结果表明,经超声处理后合成的FeAPO-11分子筛样品的晶粒大小分布更均匀,平均粒径明显降低。     

基于凸松弛方法的医学 B 超图像快速分割

利用活动轮廓线方法进行图像分割的一个重要缺陷是目标函数是非凸的, 这不仅使得分割结果容易陷于局部极小, 而且还使得一些快速算法无法开展.本文首先从贝叶斯风险估计的方法出发,针对B超幅度图像, 给出一种基于Rayleigh分布的活动轮廓线模型. 然后结合凸松弛的方法,得到一个新的放松的凸模型.原有模型和放松后模型的关系可由定理1给出. 最后结合分裂Bregman算法, 给出基于B超分割模型的快速算法.与传统梯度下降法相比较,本文提出的算法不仅能得到全局最优解,而且在算法收敛速度上也 大大优于梯度下降法.     

基于ARM和FPGA的高扩展性超声检测模块设计与实现

介绍了一种以ARM和FPGA联合作为中央控制处理单元的4路超声探伤模块。给出了其整体结构方案,阐述了以4路超声模拟信号为一组的多路超声探伤模块硬件扩展的设计思路和实现方案,讨论了FPGA对高速LVDS数据的采集、处理、时序同步功能的实现,ARM与FPGA之间总线接口的实现,ARM嵌入式系统功能以及网络通信功能的实现。实际应用表明,该功能模块能达到预期的设计要求,并能方便地实现硬件扩展。     

基于CAN总线的分布式超声形变监测系统

针对目前形变监测技术难以对大型地下围压空间形变实现大面积覆盖性监测的问题,提出一种基于CAN总线的分布式超声形变监测系统.该系统包含超声传感器单元、FPGA采集处理系统、CAN总线通信系统、上位机监控管理中心及形变评估算法模型.实验结果表明,该系统具有在线测量等特性,可实现大面积覆盖性形变监测.     

基于对数压缩的超声各向异性扩散去噪方法

针对当前超声图像去噪算法很难同时做到降噪和边缘保持的情况,在进行各向异性扩散模型研究的基础上,提出基于对数压缩的改进各向异性扩散算法（LCAD）去除超声散斑噪声。算法将图像对数压缩后进行噪声分布模型估计,然后构造基于广义伽马分布的扩散系数,在扩散过程中达到降噪和边缘保持效果。     

基于时／空滤波噪声抑制算法和活动轮廓模型的血管内超声图像边缘提取

为解决血管内超声（IVUS）图像中严重的血液斑点噪声影响边缘提取方法的有效性问题，采用一种时／空滤波方法对IYUS图像进行降噪预处理，基于活动轮廓模型（Snake模型）和IVUS图像的边缘对比度特征量，利用Hopfield神经网络并结合模拟退火算法自动提取IVUS图像的冠脉血管壁内、外膜边缘．实验结果表明，该方法对序列IVUS图像处理有较好的可重复性和鲁棒性．     

物理场处理对葵花油脂肪酸组成影响的研究

主要讨论了超声场和微波场处理对葵花油脂肪酸的影响,并用气-质联用色谱分别检测了未经处理的和经物理场处理的葵花油的脂肪酸组成和相对含量.结果表明,超声波和微波处理对葵花油的脂肪酸组成和相对含量有一定影响,但影响不显著.