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Fusing electrical and elasticity imaging
arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2020-10-14 , DOI: arxiv-2010.06847 Andreas Hauptmann and Danny Smyl
arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2020-10-14 , DOI: arxiv-2010.06847 Andreas Hauptmann and Danny Smyl
Electrical and elasticity imaging are promising modalities for a suite of
different applications including medical tomography, non-destructive testing,
and structural health monitoring. These emerging modalities are capable of
providing remote, non-invasive, and low cost opportunities. Unfortunately, both
modalities are severely ill-posed nonlinear inverse problems, susceptive to
noise and modelling errors. Nevertheless, the ability to incorporate
complimentary data sets obtained simultaneously offers mutually-beneficial
information. By fusing electrical and elastic modalities as a joint problem we
are afforded the possibility to stabilise the inversion process via the
utilisation of auxiliary information from both modalities as well as joint
structural operators. In this study, we will discuss a possible approach to
combine electrical and elasticity imaging in a joint reconstruction problem
giving rise to novel multi-modality applications for use in both medical and
structural engineering.
中文翻译:
融合电学和弹性成像
电和弹性成像是一系列不同应用的有前途的方式,包括医学断层扫描、无损检测和结构健康监测。这些新兴模式能够提供远程、非侵入性和低成本的机会。不幸的是,这两种模态都是严重不适定的非线性逆问题,容易受到噪声和建模错误的影响。然而,合并同时获得的互补数据集的能力提供了互惠互利的信息。通过将电模态和弹性模态融合为一个联合问题,我们可以通过利用来自两种模态和联合结构算子的辅助信息来稳定反演过程。在这项研究中,
更新日期:2020-10-15
中文翻译:
融合电学和弹性成像
电和弹性成像是一系列不同应用的有前途的方式,包括医学断层扫描、无损检测和结构健康监测。这些新兴模式能够提供远程、非侵入性和低成本的机会。不幸的是,这两种模态都是严重不适定的非线性逆问题,容易受到噪声和建模错误的影响。然而,合并同时获得的互补数据集的能力提供了互惠互利的信息。通过将电模态和弹性模态融合为一个联合问题,我们可以通过利用来自两种模态和联合结构算子的辅助信息来稳定反演过程。在这项研究中,