Doyley Marvin M, Srinivasan Seshadri, Dimidenko Eugene, Soni Nirmal, Ophir Jonathan
Dartmouth Medical School, Dartmouth College, Hanover, NH 03766, USA.
Phys Med Biol. 2006 Jan 7;51(1):95-112. doi: 10.1088/0031-9155/51/1/007. Epub 2005 Dec 15.
Model-based elastography is fraught with problems owing to the ill-posed nature of the inverse elasticity problem. To overcome this limitation, we have recently developed a novel inversion scheme that incorporates a priori information concerning the mechanical properties of the underlying tissue structures, and the variance incurred during displacement estimation in the modulus image reconstruction process. The information was procured by employing standard strain imaging methodology, and introduced in the reconstruction process through the generalized Tikhonov approach. In this paper, we report the results of experiments conducted on gelatin phantoms to evaluate the performance of modulus elastograms computed with the generalized Tikhonov (GTK) estimation criterion relative to those computed by employing the un-weighted least-squares estimation criterion, the weighted least-squares estimation criterion and the standard Tikhonov method (i.e., the generalized Tikhonov method with no modulus prior). The results indicate that modulus elastograms computed with the generalized Tikhonov approach had superior elastographic contrast discrimination and contrast recovery. In addition, image reconstruction was more resilient to structural decorrelation noise when additional constraints were imposed on the reconstruction process through the GTK method.
基于模型的弹性成像由于逆弹性问题的不适定性而充满问题。为克服这一限制，我们最近开发了一种新颖的反演方案，该方案纳入了有关基础组织结构力学特性的先验信息，以及在模量图像重建过程中位移估计期间产生的方差。该信息通过采用标准应变成像方法获取，并通过广义蒂霍诺夫方法引入重建过程。在本文中，我们报告了在明胶模型上进行的实验结果，以评估使用广义蒂霍诺夫（GTK）估计准则计算的模量弹性图相对于使用未加权最小二乘估计准则、加权最小二乘估计准则和标准蒂霍诺夫方法（即无模量先验的广义蒂霍诺夫方法）计算的模量弹性图的性能。结果表明，使用广义蒂霍诺夫方法计算的模量弹性图具有卓越的弹性成像对比度辨别能力和对比度恢复能力。此外，当通过GTK方法对重建过程施加额外约束时，图像重建对结构去相关噪声更具弹性。
