Department of Mathematics, Konkuk University, Seoul 143-701, Korea.
IEEE Trans Med Imaging. 2009 Oct;28(10):1526-33. doi: 10.1109/TMI.2009.2019823.
Magnetic resonance elastography (MRE) is an imaging modality capable of visualizing the elastic properties of an object using magnetic resonance imaging (MRI) measurements of transverse acoustic strain waves induced in the object by a harmonically oscillating mechanical vibration. Various algorithms have been designed to determine the mechanical properties of the object under the assumptions of linear elasticity, isotropic and local homogeneity. One of the challenging problems in MRE is to reduce the noise effects and to maintain contrast in the reconstructed shear modulus images. In this paper, we propose a new algorithm designed to reduce the degree of noise amplification in the reconstructed shear modulus images without the assumption of local homogeneity. Investigating the relation between the measured displacement data and the stress wave vector, the proposed algorithm uses an iterative reconstruction formula based on a decomposition of the stress wave vector. Numerical simulation experiments and real experiments with agarose gel phantoms and human liver data demonstrate that the proposed algorithm is more robust to noise compared to standard inversion algorithms and stably determines the shear modulus.
磁共振弹性成像（MRE）是一种利用磁共振成像（MRI）测量物体中横向声应变波的方法，该方法可以可视化物体的弹性特性，这些应变波是由物体中谐波机械振动引起的。已经设计了各种算法来确定物体在假设的线性弹性、各向同性和局部均匀性下的力学性质。MRE 中的一个具有挑战性的问题是减少噪声影响并在重建的剪切模量图像中保持对比度。在本文中，我们提出了一种新算法，该算法旨在在不假设局部均匀性的情况下降低重建剪切模量图像中的噪声放大程度。通过研究测量位移数据与应力波矢量之间的关系，所提出的算法使用基于应力波矢量分解的迭代重建公式。琼脂糖凝胶体模和人体肝脏数据的数值模拟实验和实际实验表明，与标准反演算法相比，所提出的算法对噪声更稳健，并且能够稳定地确定剪切模量。
