Banerjee B, Roy D, Vasu R M
Structures Laboratory, Department of Civil Engineering, Indian Institute of Science, Bangalore 560 012, India.
Phys Med Biol. 2009 Jan 21;54(2):285-305. doi: 10.1088/0031-9155/54/2/008. Epub 2008 Dec 16.
We propose a pseudo-dynamic form of a sub-optimal Kalman filter for elastography of plane-strain models of soft tissues under strictly static deformations and partial measurements. Since the tissue material is nearly incompressible and is thus prone to volumetric locking via standard displacement-based finite element formulations, we use a Cosserat point approach for deriving the static equilibrium equations. A pseudo-dynamical form of the equilibrium equations, with added noise and appropriate augmentation by the discretized shear modulus as additional states, is then adopted as the process equation such that its steady-state solution approaches the static response of the plane-strain model. A fictitious noise of small intensity is also added to the measurement equation and, following linearization of the process equation, a Kalman filter is applied to reconstruct the shear modulus profile. We present several numerical experiments, some of which also bring forth the relative advantages of the proposed approach over a deterministic reconstruction based on a quasi-Newton search.
我们提出了一种次优卡尔曼滤波器的伪动态形式,用于在严格静态变形和部分测量下对软组织平面应变模型进行弹性成像。由于组织材料几乎不可压缩,因此通过基于标准位移的有限元公式容易出现体积锁定,我们使用柯西拉点方法来推导静态平衡方程。然后,将平衡方程的伪动态形式,加上噪声并通过离散化的剪切模量作为附加状态进行适当扩充,作为过程方程,使其稳态解接近平面应变模型的静态响应。还向测量方程中添加了小强度的虚拟噪声,并且在对过程方程进行线性化之后,应用卡尔曼滤波器来重建剪切模量分布。我们展示了几个数值实验,其中一些还揭示了所提出方法相对于基于拟牛顿搜索的确定性重建的相对优势。