Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland.
Department of Computer Science, University College London, London, UK.
Philos Trans A Math Phys Eng Sci. 2021 Jun 28;379(2200):20200194. doi: 10.1098/rsta.2020.0194. Epub 2021 May 10.
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 datasets obtained simultaneously offers mutually beneficial information. By fusing electrical and elastic modalities as a joint problem, we are afforded the possibility to stabilize the inversion process via the utilization 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. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.
电成像和弹性成像在一系列不同的应用中具有广阔的前景，包括医学层析成像、无损检测和结构健康监测。这些新兴的模态能够提供远程、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反问题，容易受到噪声和建模误差的影响。然而，能够同时合并补充数据集提供了互惠互利的信息。通过将电成像和弹性成像作为一个联合问题进行融合，我们可以通过利用来自两种模态以及联合结构算子的辅助信息来稳定反演过程。在这项研究中，我们将讨论一种可能的方法，即将电成像和弹性成像结合在一个联合重建问题中，从而为医学和结构工程领域的新的多模态应用提供可能性。本文是专题“协同层析图像重建：第 1 部分”的一部分。
