INVERSE FINITE ELEMENT BASED ANISOTROPIC MATERIAL PROPERTY RECONSTRUCTION METHO

基于逆有限元的各向异性材料性能重构方法

• 批准号: 8171945
• 负责人: Ravi Namani
• 金额: $ 0.11万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8171945
• 关键词: Algorithms; Computer Retrieval of Information on Scientific Projects Database; Elements; Freedom; Funding; Goals; Grant; Institution; Measurement; Measures; Methods; Modeling; Property; Research; Research Personnel; Resources; Simulate; Solutions; Source; Speed; Time; United States National Institutes of Health; base; multicore processor; reconstruction; research study; soft tissue

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 goal of the proposed project is to obtain anisotropic elastic properties of soft tissues from shear wave displacement measurements. This will be achieved by first simulating the forward problem with the finite element method i.e. shear wave propagation in an elastic material. Second, an inverse method will be setup based on measured displacements from elastography experiments and predicted displacements from the forward problem. The inverse finite element model will be solved by minimizing an error function based on measured and predicted displacements by correcting for the anisotropic material parameters. Solving the inverse finite element model is a computationally intensive task due to (a) large number of degrees of freedom (usually > 10,000) in the finite element model (b) the large number of unknown material parameters that need to be solved for in the inverse problem. The inverse solution will require multiprocessor hardware and parallel algorithms to enhance the speed of solution of the inverse problem. We propose to implement macro-level parallelization of the inverse algorithm through subzone based domain decomposition to reduce the number of degrees of freedom treated at one time on each processor to tractable levels. With suitable multiprocessor hardware the proposed algorithms potentially reduce the computational time without sacrificing parameter accuracy.

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 该项目的目标是从剪切波位移测量中获得软组织的各向异性弹性特性。这将通过首先用有限元法模拟正问题来实现，即弹性材料中的剪切波传播。其次，将建立基于弹性成像实验的测量位移和正问题的预测位移的逆方法。通过校正各向异性材料参数，将基于测量和预测位移的误差函数最小化，从而求解逆有限元模型。由于（a）有限元模型中的大量自由度（通常> 10，000）（B）需要在逆问题中求解的大量未知材料参数，求解逆有限元模型是计算密集型任务。逆解需要多处理器硬件和并行算法来提高逆问题的解的速度。我们建议通过基于分区的区域分解来实现逆算法的宏观级并行化，以减少在每个处理器上一次性处理的自由度的数量到易于处理的水平。与合适的多处理器硬件，所提出的算法可能会减少计算时间，而不牺牲参数的准确性。