C-V模型与工业CT相结合的几何测量方法

针对工业生产中复杂封闭内腔几何尺寸很难测量的问题,提出一种基于C-V模型的工业CT几何测量方法.首先利用C-V模型提取目标边缘坐标点的有序链码,然后利用Green定理和欧氏距离公式计算目标区域的面积和周长.在提取目标边缘坐标点的步骤中,把边缘灰度先验知识融入C-V模型以提高测量精度;在计算目标区域的面积和周长的过程中,合理地选择目标边缘有序坐标点和插值有序坐标点,再一次提高几何测量精度.实验结果表明,与2DFacet模型测量方法相比,文中方法测量精度约提高1个数量级;并已将该方法应用于实际中.     

电容耦合电阻层析成像传感器结构优化设计研究

针对电容耦合电阻层析成像传感器的优化设计,首先利用有限元仿真软件建立了12电极传感器有限元模型,并分析了后续图像重建所需的传感器灵敏场,之后将该仿真模型与实际传感器相应的测量数据及重建图像进行对比验证,研究表明仿真与实验结果能够较好吻合,为对传感器性能进一步研究提供可靠基础.为了提高系统稳定性及抗干扰能力,以该原始模型...     

基于网络断层扫描的传感器网络链路丢包研究

文中提出了一种基于网络断层扫描的无线传感器网络链路丢包率测量方法,通过边界节点的丢包率来估计传感器内部链路丢包的情况。根据无线传感器网络数据聚合的特点,提出了网络逻辑拓扑和链路报文丢包模型,在将链路报文丢失率推测问题形式化为MLE问题的基础上,用引入修正因子的μ的EM算法来推测链路报文丢失率。NS2仿真结果证明,μ-EM算法推测的链路报文丢失率与预设值更加接近,特别是在大规模网络中μ-EM算法在精确度和有效性方面均明显优于EM算法。     

基于XCT扫描图像的混凝土二维细观受压断裂模拟

为了研究混凝土细观层次断裂力学特性,对混凝土试件进行原位XCT扫描,基于扫描图像提出了具有真实内部结构特征的混凝土二维细观模型,并预先在水泥砂浆和骨料-水泥砂浆界面插入零厚度粘结裂缝单元用以模拟潜在的裂缝。通过对该模型进行混凝土单轴受压数值仿真模拟,讨论其裂缝的发展过程以及不同细观结构和相应参数对混凝土断裂损伤行为的影响。结果表明：数值模拟得到的混凝土二维模型抗压强度与试验测得的强度相接近;混凝土的抗压强度受到水泥砂浆和骨料-砂浆界面裂缝单元的绝对数值影响,其中水泥砂浆裂缝单元强度对材料强度起控制作用;骨料-砂浆界面裂缝单元强度与水泥砂浆裂缝单元强度的比率对裂缝衍生发展有显著影响。     

Evaluation of the Effects of Developmental Trauma on Neurotransmitter Systems Using Functional Molecular Imaging

Early life stress (ELS) is strongly associated with psychiatric disorders such as anxiety, depression, and schizophrenia in adulthood. To date, biological, behavioral, and structural aspects of ELS have been studied extensively, but their functional effects remain unclear. Here, we examined NeuroPET studies of dopaminergic, glutamatergic, and serotonergic systems in ELS animal models. Maternal separation and restraint stress were used to generate single or complex developmental trauma. Body weights of animals exposed to single trauma were similar to those of control animals; however, animals exposed to complex trauma exhibited loss of body weight when compared to controls. In behavioral tests, the complex developmental trauma group exhibited a decrease in time spent in the open arm of the elevated plus-maze and an increase in immobility time in the forced swim test when compared to control animals. In NeuroPET studies, the complex trauma group displayed a reduction in brain uptake values when compared to single trauma and control groups. Of neurotransmitter systems analyzed, the rate of decrease in brain uptake was the highest in the serotonergic group. Collectively, our results indicate that developmental trauma events induce behavioral deficits, including anxiety- and depressive-like phenotypes and dysfunction in neurotransmitter systems.     

Physiological Imaging Methods for Evaluating Response to Immunotherapies in Glioblastomas

Glioblastoma (GBM) is the most malignant brain tumor in adults, with a dismal prognosis despite aggressive multi-modal therapy. Immunotherapy is currently being evaluated as an alternate treatment modality for recurrent GBMs in clinical trials. These immunotherapeutic approaches harness the patient’s immune response to fight and eliminate tumor cells. Standard MR imaging is not adequate for response assessment to immunotherapy in GBM patients even after using refined response assessment criteria secondary to amplified immune response. Thus, there is an urgent need for the development of effective and alternative neuroimaging techniques for accurate response assessment. To this end, some groups have reported the potential of diffusion and perfusion MR imaging and amino acid-based positron emission tomography techniques in evaluating treatment response to different immunotherapeutic regimens in GBMs. The main goal of these techniques is to provide definitive metrics of treatment response at earlier time points for making informed decisions on future therapeutic interventions. This review provides an overview of available immunotherapeutic approaches used to treat GBMs. It discusses the limitations of conventional imaging and potential utilities of physiologic imaging techniques in the response assessment to immunotherapies. It also describes challenges associated with these imaging methods and potential solutions to avoid them.     

X射线ICT检测中康普顿散射效应的影响与修正

在X射线工业计算机层析检测(ICT)中,由于X射线与物质作用发生康普顿散射效应,有用信息连同散射光子一起进入探头形成伪影。运用康普顿散射强度方程,结合X射线与物质相互作用的特性,推出X射线ICT中的散射修正公式,并由圆形截面工件散射模型,求出圆形截面工件的具体计算积分限。从探测器探测到的总光子数中减去康普顿散射光子数,即可有效去除散射光子造成的伪影。     

基于电容层析成像和模糊模式识别的油气两相流流型辨识新方法的研究

基于电容层析成像和模糊模式识别技术别提出了一种油气两相流流型辨识的新方法。建立了12电极电容层析成像流型自动识别系统，该系统利用Tikhonov正则化原理并结合SIRT(Simultaneous Reconstruction Techniques)算法进行图像重建。Tikhonov正则化原理用于克服图像重建过程中的不适定问题，SIRT算法用于提高最终重建图像的质量。根据流型的随机和模糊特性，提出了一种根据管截面重建图像进行流型辨识的模糊流型判别方法。研究结果表明，提出的流型辨识新方法是有效的。对于层状流、核心流、环状流、均相流等流型，流型辨识的准确率高于95％，辨识一个流型所用的时间小于0.3秒。对于塞状流，流型辨识的准确率高于90％。     

A stochastic Kaczmarz algorithm for network tomography

We develop a stochastic approximation version of the classical Kaczmarz algorithm that is incremental in nature and takes as input noisy real time data. Our analysis shows that with probability one it mimics the behavior of the original scheme: starting from the same initial point, our algorithm and the corresponding deterministic Kaczmarz algorithm converge to precisely the same point. The motivation for this work comes from network tomography where network parameters are to be estimated based upon end-to-end measurements. Numerical examples via Matlab based simulations demonstrate the efficacy of the algorithm.     

Personalized identification of abdominal wall hernia meshes on computed tomography

An abdominal wall hernia is a protrusion of the intestine through an opening or area of weakness in the abdominal wall. Correct pre-operative identification of abdominal wall hernia meshes could help surgeons adjust the surgical plan to meet the expected difficulty and morbidity of operating through or removing the previous mesh. First, we present herein for the first time the application of image analysis for automated identification of hernia meshes. Second, we discuss the novel development of a new entropy-based image texture feature using geostatistics and indicator kriging. Third, we seek to enhance the hernia mesh identification by combining the new texture feature with the gray-level co-occurrence matrix feature of the image. The two features can characterize complementary information of anatomic details of the abdominal hernia wall and its mesh on computed tomography. Experimental results have demonstrated the effectiveness of the proposed study. The new computational tool has potential for personalized mesh identification which can assist surgeons in the diagnosis and repair of complex abdominal wall hernias.