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PSO algorithm for Young's modulus reconstruction

机译:杨氏模量重构的PSO算法

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摘要

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.
机译:为了获得异常生物组织的定量值,提出了一种基于边界提取和图像配准技术的杨氏模量逆算法。利用边界组织的已知位移和力分布,通过构造单位系统和逆有限元方法(IFEM)来计算杨氏模量。然后,参考之前获得的值来估计整个组织的模量的艰难范围。采用改进的粒子群优化算法(PSO)来计算整个杨氏模量分布。该算法克服了其他杨氏模量重构方法的一些局限性,并放宽了位移和力边界条件的要求。重复的数值模拟表明边界位移的误差对下一过程的估计不是很敏感。通过改进的PSO方法可以获得最终可行的解决方案,该方法在较大范围内接近在搜索过程中获得的理论值。

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