A quadratic optimization program for the inverse elastography problem

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-08-19 DOI:10.1186/s13362-024-00156-7

Sílvia Barbeiro, Rafael Henriques, José Luis Santos

引用次数: 0

Abstract

In this work we focus on the development of a numerical algorithm for the inverse elastography problem. The goal is to perform an efficient material parameter identification knowing the elastic displacement field induced by a mechanical load. We propose to define the inverse problem through a quadratic optimization program which uses the direct problem formulation to define the objective function. In this way, we end up with a convex minimization problem which attains its minimum at the solution of a linear system. The effectiveness of our method is illustrated through numeral examples.

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反弹性成像问题的二次优化程序

在这项工作中，我们重点开发了一种用于反弹性成像问题的数值算法。我们的目标是在了解机械载荷引起的弹性位移场的情况下，进行有效的材料参数识别。我们建议通过二次优化程序来定义逆问题，该程序使用直接问题公式来定义目标函数。这样，我们就得到了一个凸最小化问题，该问题在线性系统的解中达到最小值。我们将通过数字示例来说明我们方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.