Monte Carlo方法在扩散光学成像仿真中的应用

综述了描述前向问题的各种模型,包括解析解方法、数值方法和统计方法.特别地,就生物自发光多谱段光源的实例介绍了Monte Carlo方法.在光学成像领域,针对不同的成像模态、对成像质量的要求以及所需要的信息,MC方法有3种主要形式:连续波、时域和频域.不仅揭示了每种形式的基本原理,同时也相应地介绍了其在本领域的典型应用及软件.通过这些应用可以看出,MC方法对于扩散光学成像,特别是最近几年的在体无创实时成像的发展发挥着重要作用.     

在体生物光学成像技术的研究进展

在体生物发光成像和在体荧光成像是近年来新兴的在体生物光学成像技术, 能够无损实时动态监测被标记细胞在活体小动物体内的活动及反应, 在肿瘤检测、基因表达、蛋白质分子检测、药物受体定位、药物筛选和药物疗效评价等方面具有很大的应用潜力. 本文详细介绍了在体生物发光成像和在体荧光成像的特点、系统及应用, 比较了它们的异同, 综述了在体生物光学成像技术的基本原理和应用领域, 讨论了将其应用于临床的进一步发展方向.     

基于多角度光学投影表面重建的三维自发荧光光源定位算法

在自发荧光断层成像（Bioluminescent tomography imaging,BLT）中,双模态融合（光学模态与结构模态）可充分利用结构模态提供的高精度3D几何结构,重建三维表面荧光光通量分布,进而实现小动物内部荧光光源定位.然而,与纯光学模态相比,双模态融合存在采集系统复杂、成本高、数据处理繁琐及存在电离辐射（如CT）等问题.因此,研究基于纯光学3D几何结构的自发荧光光源定位方法对BLT具有重要意义. 本文在搭建纯光学自发荧光断层系统（All-optical bioluminescence tomography system,AOBTS）的基础上,提出一种基于多角度光学投影表面重建的三维自发荧光光源定位方法. 本方法由基于多角度光学投影的3D表面重建、多角度荧光无缝融合、荧光光通量的量化校正以及自发荧光内部光源重建4部分组成. 通过真实小鼠内部植入荧光光源实验表明,与传统纯光学方法相比,本文提出方法不仅改进了3D表面重建方法,而且增加了多角度荧光无缝融合,可实现真实小鼠的三维自发荧光光源定位,初步实验证明具有小动物预临床实验潜力.     

一种生物在体荧光成像的自适应分割算法

生物在体荧光成像是新兴分子影像技术中性能高、费用低、前景好的一种成像模态。针对生物在体荧光图像的特点和应用需求,提出一种全新的自适应图像分割算法。通过对荧光图像的归一化处理、连通性操作、感兴趣区域区分实现自适应分割。实验结果表明,该算法能够在弱信号、低信噪比、多光源的情况下得到较理想的分割结果,是一种有效的荧光图像分割算法。     

序贯Monte Carlo算法仿真结果分析

序贯Monte Carlo方法能够解决很多实际问题.它的系统模型与Kalman滤波算法相比具有更广泛的适用性,所以研究Monte Carlo方法是很有实际意义的.文中对序贯Monte Carlo算法进行性能分析,对这一方法的跟踪能力进行了仿真实验.采用的仿真系统模型是非线性系统模型.仿真实验比较了EKF、SIS、SIR算法的性能.通过对不同算法的仿真结果之间的分析和比较,得出了有意义的结论.这对一些工程问题的解决是有重要意义的.     

不变结构半弹道式再入飞行器的混合状态估计与模型集设计

多模型方法是混合估计的主流方法之一,以该方法估计不变结构半弹道式再入飞行器(SBRV)混合状态的难点在于设计有效的模型集.文中提出了一种伪Monte Carlo模型集可以使SBRV混合状态估计器在最小均方差(MMSE)意义下接近于最优.SBRV的再入估计具有高度的非线性,同时其模式由多个边界已知的参数张成.给出了这种伪Monte Carlo模型集的设计方法,并分析了其性能特征.该模型集相比于Monte Carlo方法生成的模型集有更高的精度,理论分析和仿真结果表明了新设计模型集的有效性与合理性.     

活体光学投影断层成像系统与应用

光学投影断层成像（Optical projection tomography,OPT）技术可以对1～10mm 尺度的低散射生物样本进行激发成像,具有微米级的空间分辨率、无辐射、成本低等特点,为小尺寸生物样本的高分辨率三维成像提供了一种新的手段. OPT最早通过对离体生物组织如小鼠胚胎、小鼠器官等成像,进行药物疗效评估、基因表达等研究,但是离体成像不能动态、完整地反映生物组织的变化,因此活体成像技术逐渐成为OPT领域的研究热点.本文详细介绍了我们自主研发的活体OPT系统,该成像系统以准直激光器为光源单元,高精密移动和旋转 电控平台为样本定位单元,低温电子倍增（Electron multiplying,EM） CCD探测器为采集单元,实现了针对果蝇蛹等小模式动物的活体三维成像.该系统的空间分辨率优于10 μm,成像视野1～10mm,扫描时间小于2min,重建时间小于5s.最后,本文通过果蝇蛹的三维活体成像实验展示该系统的操作流程、成像结果和初步的生物应用.     

光纤生物传感器系统中光纤连接器的性能分析与优化设计

在已构建的全光纤结构生物传感器的基础上,对系统中关键器件--光纤连接器中的信号收集效率和噪声进行了理论分析.针对荧光信号传输的特点,采用光纤端面光强均匀分布的模型,运用重叠面积积分的方法推导出计算信号耦合效率的公式,计算了各种连接器结构下的信号耦合率,以求达到最好的接收效果.并分析了主要噪声的影响,通过建立的模型,给出了抑制噪声的方法和结构参数.最后根据实验得到的结果,分析了现有系统的连接器,并提出了改进方法.     

反馈未知闭环系统的MRIV法辨识

本文提出了一种改进的精致辅助变量法.这种方法适合于反馈未知的闭环系统的参数 估计.本文在理论上分析了此方法的一致性,并通过Monte Carlo仿真实验证实了方法的 有效性.     

微米孔阵列振幅型光子筛的设计和制作

在软X射线波段,各种材料的折射率均接近或小于1,常规的折射光学元件将无法使用,但是可以用光子筛等新型衍射光学元件实现软X射线波段的聚焦、成像和色散.光子筛具有体积小、重量轻、易复制和特殊的光学性能等优点,可以构成微型光机电集成系统(MOEMS),有效提高器件效能,降低成本,在军事、工业和民用等方面,应用市场潜力很大.综述了光子筛的国内外研究进展,介绍了光子筛的成像原理,根据标量衍射理论探讨了低数值孔径振幅光子筛的基本设计方法和制作工艺,给出了光子筛的计算机仿真结果,并且用激光直写方法在镀铬石英基片上刻蚀了特征尺寸为5 μm的微米孔阵列光子筛,实验测试了光子筛的成像性能.     

A microwave propagation model for estimation of effective attenuation coefficients in a vegetation canopy

This article presents a detailed theoretical model for propagation of microwave in a layer of vegetation medium. The vegetation medium is modeled by a layer of randomly distributed dielectric circular disks and cylinders, representing the leaves and the stems, respectively. Propagation of wave in such a medium is taken as a transport of energy problem, and is formulated by a Monte Carlo method. Interactions of wave with the vegetation components are treated as a sequence of multiple scattering events between the photon flux and the scatterers. A Monte Carlo algorithm is used to track these collision processes, and the energy of the photon leaving the vegetation layer is collected. With sufficient number of photon histories, the ensemble averages of the photon energy are used to calculate the attenuation coefficients of the wave through the vegetation layer. Our simulation results indicate that attenuation coefficients calculated using this multiple scattering model may differ from those given by a simple single scattering model. Effects on the attenuation coefficients by various parameters such as moisture content, scatterer's size, and volume fraction are studied. Comparisons of the calculated results are made with the measured data and good match is obtained.     

Mathematical simulation of ultrashort light pulse propagation in a highly scattering medium

The problem of probing a nonhomogeneous medium imitating the biological tissue by an ultrashort light pulse is investigated. The pulse propagation in the medium is described by a transient transport equation. A grid algorithm for its solution based on the analytical presentation of the density of the unscattered photon flux is presented as well as a semianalytical algorithm for computing the density of the flux of singly scattered photons. Methodological calculations carried out by the grid method and by the alternative Monte Carlo method are given.     

Light transport in tissue by 3D Monte Carlo: influence of boundary voxelization

Monte Carlo (MC) based simulations of photon transport in living tissues have become the "gold standard" technique in biomedical optics. Three-dimensional (3D) voxel-based images are the natural way to represent human (and animal) tissues. It is generally believed that the combination of 3D images and MC based algorithms allows one to produce the most realistic models of photon propagation. In the present work, it is shown that this approach may lead to large errors in the MC data due to the "roughness" of the geometrical boundaries generated by the presence of the voxels. In particular, the computed intensity of the light detected on the tissue surface of a simple cubic tissue phantom may display errors from -80% to 120%. It is also shown that these errors depend in a complex manner on optical and geometrical parameters such as the interoptode distance, scattering coefficient, refractive index, etc. and on the degree of voxelization ("roughness") of the boundaries. It is concluded that if one wants to perform reliable 3D Monte Carlo simulations on complex geometries, such as human brain, skin or trabecular bone, it is necessary to introduce boundary meshing techniques or other equivalent procedures in the MC code to eliminate the deleterious effect of voxelization.     

Monte Carlo modeling of time-resolved fluorescence for depth-selective interrogation of layered tissue

Computational approaches for simulation of light-tissue interactions have provided extensive insight into biophotonic procedures for diagnosis and therapy. However, few studies have addressed simulation of time-resolved fluorescence (TRF) in tissue and none have combined Monte Carlo simulations with standard TRF processing algorithms to elucidate approaches for cancer detection in layered biological tissue. In this study, we investigate how illumination-collection parameters (e.g., collection angle and source-detector separation) influence the ability to measure fluorophore lifetime and tissue layer thickness. Decay curves are simulated with a Monte Carlo TRF light propagation model. Multi-exponential iterative deconvolution is used to determine lifetimes and fractional signal contributions. The ability to detect changes in mucosal thickness is optimized by probes that selectively interrogate regions superficial to the mucosal-submucosal boundary. Optimal accuracy in simultaneous determination of lifetimes in both layers is achieved when each layer contributes 40-60% of the signal. These results indicate that depth-selective approaches to TRF have the potential to enhance disease detection in layered biological tissue and that modeling can play an important role in probe design optimization.     

Methods for uncertainty propagation in life cycle assessment

Life cycle assessment (LCA) calculates the environmental impact of a product over its entire life cycle. Uncertainty analysis is an important aspect in LCA, and is usually performed using Monte Carlo sampling. In this study, Monte Carlo sampling, Latin hypercube sampling, quasi Monte Carlo sampling, analytical uncertainty propagation and fuzzy interval arithmetic were compared based on e.g. convergence rate and output statistics. Each method was tested on three LCA case studies, which differed in size and behaviour. Uncertainty propagation in LCA using a sampling method leads to more (directly) usable information compared to fuzzy interval arithmetic or analytical uncertainty propagation. Latin hypercube and quasi Monte Carlo sampling provide more accuracy in determining the sample mean than Monte Carlo sampling and can even converge faster than Monte Carlo sampling for some of the case studies discussed in this paper.     

ANN modeling of the bremsstrahlung photon flux in tantalum target

Bremsstrahlung photons produced by 15 MeV electron beam are simulated using the Monte Carlo code of FLUKA. Tantalum foils have been chosen as a target material in the simulation, and the obtained photon spectrum has been analyzed with artificial neural network (ANN) technique. In the training ANN model, the thicknesses and energy values of bremsstrahlung photons for the Ta target have been used as input. In this study, we observed that the trained ANN model is consistent with simulation results.     

Application of the finite-element method for the forward and inverse models in optical tomography

The development of an optical tomographic imaging system for biological tissue based on time-resolved near-infrared transillumination has received considerable interest recently. The reconstruction problem is ill posed because of scatter-dominated photon propagation, and hence it requires both an accurate and fast transport model and a robust solution convergence scheme. The iterative image recovery algorithm described in this paper uses a numerical finite-element solution to the diffusion equation as the photon propagation model. The model itself is used to compare the influence of absorbing and scattering inhomogeneities embedded in a homogeneous tissue sample on boundary measurements to estimate the possibility of separating absorption and scattering images. Images of absorbers and scatterers reconstructed from both mean-time-of-flight and logarithmic intensity data are presented. It is found that mean-time-of-flight data offer increased resolution for reconstructing the scattering coefficient, whereas intensity data are favorable for reconstructing absorption.     

An Algorithmic Reflectance and Transmittance Model for Plant Tissue

Recent developments in rendering have provided very realistic images. However, these images rarely show organic objects. We believe that one of the main difficulties of rendering these objects realistically is the lack of reflectance and transmittance models oriented to organic materials. In this paper an algorithmic reflectance and transmittance model for plant tissue oriented to computer graphics applications is presented. The model accounts for the three components of light propagation in plant tissues, namely surface reflectance, subsurface reflectance and transmittance, and mechanisms of light absorption by pigments present in these tissues. The model design is based on the available biological information, and it is controlled by a small number of biologically meaningful parameters. Its formulation, based on standard Monte Carlo techniques, guarantees its easy incorporation into most rendering systems. The spectral curves of reflectance and transmittance computed by the model are compared with measured curves from actual experiments.     

自发荧光成像中光子传输蒙卡仿真的并行实现

在生物自发光成像领域,将基于蒙特卡罗方法的光子前向传输仿真进行并行化,提高了仿真的速度。首先介绍了所采用的一系列并行机制和串行加速算法,然后分别对并行仿真结果进行正确性验证和性能验证,并与软件MOSE、triMC3D的结果进行了对比,最后对该并行平台进行了总结和展望。