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Two-Level Multiplicative Domain Decomposition Algorithm for Recovering the Lame Coefficient in Biological Tissues

机译:用于回收生物组织跛足系数的两级乘法域分解算法

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Tissue stiffness is one of the qualitative properties to distinguish abnormal tissues from normal tissues, and the stiffness changes are generally described in terms of the Lame coefficient. In this paper, an all-at-once Lagrange-Newton-Krylov-Schwarz algorithm is developed to solve the inverse problem of recovering the Lame coefficient in biological tissues. Specifically, we propose and study a multiplicative two-level domain decomposition preconditioner in the inexact Newton step. Numerical experiments are presented to show the efficiency and scalability of the algorithm on supercomputers.
机译:组织刚度是区分正常组织的异常组织的定性性质之一,并且通常在跛足系数方面描述刚度变化。在本文中,开发了全面的Lagrange-Newton-Krylov-Schwarz算法以解决恢复生物组织中跛足系数的逆问题。具体而言,我们提出并研究了一个乘法的两级域分解预处理器,在Inexact Newton步骤中。提出了数值实验以显示超级计算机上算法的效率和可扩展性。

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