Systematic FEMSS of Soft Tissue Viscoelasticity

提出的基于有限元模型的状态空间（FEMSS）的假设是，给定活组织中的位移是已知的（可以通过MRI，超声等提供），然后我们可以表征其弹性和粘性特性。FEMSS不是基于特定的成像技术来获取位移。在这个项目中，我们将开发一个超声波阵列，以便在内部对模型进行即时关联和验证，我们将使用MRI图像来关联我们的数据。为了实现我们的目标，我们建议(a)研究软组织的线性和非线性固体动力学模型，(b)对测量和我们的系统中呈现的不确定性进行建模和表征，(c)开发一个虚拟实验室，以及(d)实验验证和微调。我们将通过在实验室进行的实验来微调我们的FEMSS模型。如果成功，所提出的工作将提供一个一致的，统一的数学模型，用于解决活体组织的非侵入性表征的正向问题。我们预计这项工作将为癌症研究、远程手术和体育运动中的组织诊断创造有利的技术。此外，这个多学科项目将引入材料科学、生物工程、微纳米测量、几何材料建模控制、高科技计算技术和图像处理等方面的任务，以开发一种最先进的组织诊断工具，具有独特的定量测量能力，并以数学方式全面描述。研究生和本科生将接受最先进的计算和实验技术的培训。我们将积极合作和培训少数民族学生，我们将扩大到当地社区，以教育公众在生物医学应用中使用材料建模。结果将通过互联网、期刊和会议传播。

Abstract CMMI - 0900596The hypothesis for the proposed finite element model based state space (FEMSS) is that given that the displacements in a living tissue are known (can be provided via MRI, ultrasound etc.) then we can characterize its elastic and viscous properties. The FEMSS is not based on a particular imaging technique in order to acquire the displacements. During this project we will develop an ultrasound array so as to have immediate correlation and validation of the model in house, and we will use MRI images to correlate our data. In order to achieve our goal we propose to (a) Investigate linear and non-linear solid dynamics models for soft tissues, (b) Model and characterize of uncertainties presented in measurements and our system, (c) Develop a phantom virtual laboratory, and to (d) Experimental validation and fine tuning. We will fine-tune our FEMSS model with experiments performed in our labs.If successful the proposed work will provide a consistent, unitary mathematical model for the solution of the forward problem for the non-invasive characterization of living tissues. We anticipate that this work will create enabling technologies for tissue diagnostics with applications in cancer research, remote surgery and athletics. Moreover this multidisciplinary program will bring in tasks from materials science, bioengineering, micro & nano measurements, geometric & material modeling controls, hi-tech computational techniques, and image processing to develop a state of the art tissue diagnostic tool, with unique quantitative measuring capabilities and that is described mathematically to its entirety. Graduate and undergraduate students will be trained in state of the art computational and experimental techniques. We will actively collaborate and train minority students and we will outreach to local communities in order to educate the public about the use of materials modeling in biomedical applications. Results dissemination will occur via internet, journals and conferences.