TRANSPORT COMPUTATIONAL METHODS

运输计算方法

• 批准号: 7722504
• 负责人: Bruce J. Tromberg
• 金额: $ 0.21万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-15 至 2009-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7722504
• 关键词: Algorithms; Biology; Computer Retrieval of Information on Scientific Projects Database; Computing Methodologies; Development; Diffuse; Diffusion; Funding; Goals; Grant; Image Analysis; Institution; Lead; Learning; Length; Light; Medicine; Methodology; Methods; Modeling; Monte Carlo Method; Optics; Phase; Photons; Property; Recording of previous events; Reporting; Research; Research Personnel; Resources; Solutions; Source; Standards of Weights and Measures; Structure; Techniques; Technology; Tissues; United States National Institutes of Health; computerized data processing; design; improved; migration; millimeter; novel; programs; simulation

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The overall goals of this proposed research are to a) improve the design and application of computational methods necessary to process data obtained by optical probes and b) extend our capacity to analyze and image heterogeneous tissue structures on sub-millimeter to centimeter length scales. The vast majority of methodologies currently used to model the transport of light in tissue (the forward problem) and to determine the optical properties of heterogeneous tissue structures (the inverse problem) rely heavily on standard or enhanced optical diffusion models, supplemented by the occasional use of detailed Monte Carlo simulations. We are developing advanced Monte Carlo methods that lead to faster, more accurate and, in some instances, detailed global solutions of tissue/light transport problems. Novel methods for modeling approximate solutions of both forward and inverse problems have also been developed. Effort has concentrated on the selective application of these methods to forward and inverse problems of direct relevance to LAMMP core program technologies and to related collaborative research. Reported elsewhere is recent progress on "Perturbation Monte Carlo Techniques for Diffuse Photon Transport", "Monte Carlo Modeling for Diffuse Photon Migration", and "Condensed History Monte Carlo Algorithms". Here we report on a recent breakthrough in the development of adaptive Monte Carlo algorithms (i.e., algorithms capable of learning that achieve geometric convergence for general transport problems. We have discovered a new geometrically convergent method for estimating the averages of the detailed space-angle distribution of light over arbitrary decompositions of the tissue phase space. This new technique has great potential for bringing accurate radiative transport computational methods into more routine use for biomedical and other applications in biology and medicine.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目及 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 这项研究的总体目标是a）改进处理光学探针获得的数据所需的计算方法的设计和应用，b）扩展我们在亚毫米到厘米长度尺度上分析和成像异质组织结构的能力。 目前用于模拟组织中的光传输（正向问题）和确定异质组织结构的光学特性（逆向问题）的绝大多数方法在很大程度上依赖于标准或增强的光学扩散模型，并偶尔使用详细的蒙特卡罗模拟。 我们正在开发先进的蒙特卡罗方法，这些方法可以为组织/光传输问题提供更快、更准确、在某些情况下更详细的全局解决方案。还开发了对正向和逆向问题的近似解进行建模的新方法。 我们的努力集中在有选择地应用这些方法来解决与 LAMMP 核心项目技术和相关协作研究直接相关的问题。 其他地方报道了“漫射光子传输的扰动蒙特卡罗技术”、“漫射光子迁移的蒙特卡罗建模”和“简明历史蒙特卡罗算法”的最新进展。在这里，我们报告了自适应蒙特卡罗算法（即能够学习并实现一般运输问题的几何收敛的算法）开发的最新突破。我们发现了一种新的几何收敛方法，用于估计详细空间角度分布的平均值这项新技术具有巨大的潜力，可以将精确的辐射传输计算方法带入生物医学和生物学和医学的其他应用中。