NANAAPFAJan 19, 2018

Lamé Parameter Estimation from Static Displacement Field Measurements in the Framework of Nonlinear Inverse Problems

arXiv:1710.1044634 citationsh-index: 49
Originality Incremental advance
AI Analysis

For researchers in quantitative elastography, this work provides theoretical convergence guarantees for iterative regularization methods applied to a nonlinear inverse problem, though it is incremental as it extends existing theory to a specific application.

This paper addresses the estimation of Lamé parameters from static displacement field data in elastography, formulated as a nonlinear inverse problem. The authors verify a nonlinearity condition ensuring convergence of Landweber iteration and present numerical examples demonstrating recovery of parameters.

We consider a problem of quantitative static elastography, the estimation of the Lamé parameters from internal displacement field data. This problem is formulated as a nonlinear operator equation. To solve this equation, we investigate the Landweber iteration both analytically and numerically. The main result of this paper is the verification of a nonlinearity condition in an infinite dimensional Hilbert space context. This condition guarantees convergence of iterative regularization methods. Furthermore, numerical examples for recovery of the Lamé parameters from displacement data simulating a static elastography experiment are presented.

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