基于粒子群优化算法的生物组织杨氏模量的重构

为了定量求解生物病变组织的杨氏模量,提出了一种基于边缘提取技术和图像配准技术的杨氏模量反演方法.在已知生物组织边缘位移及病变边缘的基础上,根据力的分布,构造单元系统,运用有限元反演方法(IFEM),计算出组织的杨氏模量.在此基础上估计全局杨氏模量范围,采用改进粒子群优化算法(PSO),计算出生物组织整体的杨氏模量分布.该算法克服了其他杨氏模量重建算法的限制,放松了对位移和边界力的要求.通过多次数值实验得出算法对存在误差的边缘位移同样有效;改进的PSO算法在较大范围内叠代搜索,总能向理论值靠近,并得到可行解.

PSO algorithm for Young's modulus reconstruction

To get the quantitive value of abnormal biological tissues,an inverse algorithm about the Young's modulus based on the boundary extraction and the image registration technologies is proposed.With the known displacements of boundary tissues and the force distribution,the Young's modulus is calculated by constructing the unit system and the inverse finite element method (IFEM).Then a tough range of the modulus for the whole tissue is estimated referring the value obtained before.The improved particle swarm optimizer (PSO) method is adopted to calculate the whole Yong's modulus distribution.The presented algorithm overcomes some limitations in other Young's modulus reconstruction methods and relaxes the displacements and force boundary condition requirements.The repetitious numerical simulation shows that errors in boundary displacement are not very sensitive to the estimation of next process;a final feasible solution is obtained by the improved PSO method which is close to the theoretical values obtained during searching in an extensive range.