Imaging the Mechanical Properties of Soft Tissue/L'imagerie des caractéristiques mécaniques des tissus mous.

弹性成像是一种相对较新的成像软组织内弹性特性分布的技术。弹性成像提供了可视化弹性对比度的能力，乳腺癌的弹性对比度比X射线对比度大10-100倍，以及组织衰减等复杂属性，能够唯一地诊断肝纤维化。由于没有直接成像内部弹性值的方法，弹性成像依赖于三步法：首先，对组织施加机械驱动(例如振动)，产生依赖于内部弹性结构的应变场；其次，使用数字、超声或磁共振成像等方法来捕捉该应变模式；最后，通过数学反问题从测量的应变场重建弹性特性图像。这项研究计划侧重于支撑这一复杂成像过程的工程系统。目标是开发实用的工具和资源，用于在体内应用先进的弹性成像方法。这项研究计划支持的主要项目包括：开发各向异性材料特性的成像方法；改进基于数字图像的弹性成像的图像重建能力；为外部研究小组提供从3D磁共振位移数据重建弹性成像图像的在线服务；改进弹性成像图像计算的数学和统计方法；以及用于快速图像处理的图形处理器单元计算。在每种情况下，科学的方法都包括确定每个目标应用程序的关键约束和目标，例如成本、处理时间、边界条件和复杂的机械行为等问题。然后，这些约束和条件被用来驱动功能原型系统的设计和实现。通过这种方式，该计划希望建立一条管道，用于生成新的弹性成像应用程序，进而可以通过适当的外部资助机制进一步开发。

Elastography is a relatively new technology for imaging the elastic property distribution within soft tissues. Elastography offers the ability to visualize elastic contrast, 10-100X greater than x-ray contrast for breast cancer, as well complex properties such as tissue attenuation, uniquely able to diagnose liver fibrosis. As no direct method for imaging internal elasticity values exists, elastography relies on a three step approach: first, mechanical actuation (e.g. vibration) is applied to the tissue, generating a strain field that is dependent upon the internal elastic structure; second, methods such as digital, ultrasound or magnetic resonance imaging are used to capture this strain pattern; finally, the elastic property image is reconstructed from the measured strain field by means of a mathematical inverse problem. This research program focuses on the engineering systems that underlie this complex imaging process. The goal is to develop practical tools and resources for the application of advanced elastographic imaging methods in-vivo. Key projects to be supported by this research program include: development of methods for imaging anisotropic material properties; improved image reconstruction capability for digital image based elastography; an on-line service available to external research groups for elastographic image reconstruction from 3D Magnetic Resonance displacement data; improved mathematical and statistical methods for elastographic image calculation; and Graphics Processor Unit computing for fast image processing. In each case, the scientific approach consists of identifying the key constraints and objectives of each target application, e.g issues such as cost, processing time, boundary conditions, and complex mechanical behavior. These constraints and conditions are then used to drive the design and implementation of a functioning prototype system. In this way, this program looks to establish a pipeline for generating novel elastography applications, which in turn may be further developed through appropriate outside funding mechanisms.