Brazey Benoit, Haddab Yassine, Zemiti Nabil
LIRMM, Univ Montpellier, CNRS, Montpellier, France.
Proc Math Phys Eng Sci. 2022 Feb;478(2258):20210713. doi: 10.1098/rspa.2021.0713. Epub 2022 Feb 2.
Electrical impedance tomography (EIT) is a medical imaging technique with many advantages and great potential for development in the coming years. Currently, some limitations of EIT are related to the ill-posed nature of the problem. These limitations are translated on a practical level by a lack of genericity of the developed tools. In this paper, the main robust data acquisition and processing tools for EIT proposed in the scientific literature are presented. Their relevance and potential to improve the robustness of EIT are analysed, in order to conclude on the feasibility of a robust EIT tool capable of providing resistivity or difference of resistivity mapping in a wide range of applications. In particular, it is shown that certain measurement acquisition tools and algorithms, such as faulty electrode detection algorithm or particular electrode designs, can ensure the quality of the acquisition in many circumstances. Many algorithms, aiming at processing acquired data, are also described and allow to overcome certain difficulties such as an error in the knowledge of the position of the boundaries or the poor conditioning of the inverse problem. They have a strong potential to faithfully reconstruct a quality image in the presence of disturbances such as noise or boundary modelling error.
电阻抗断层成像（EIT）是一种医学成像技术，具有诸多优点，在未来几年有很大的发展潜力。目前，EIT的一些局限性与该问题的不适定性有关。这些局限性在实际层面上表现为所开发工具缺乏通用性。本文介绍了科学文献中提出的用于EIT的主要鲁棒数据采集和处理工具。分析了它们对于提高EIT鲁棒性的相关性和潜力，以便就一种能够在广泛应用中提供电阻率或电阻率差异映射的鲁棒EIT工具的可行性得出结论。特别地，结果表明某些测量采集工具和算法，如故障电极检测算法或特殊电极设计，能够在许多情况下确保采集质量。还描述了许多旨在处理采集数据的算法，这些算法能够克服某些困难，如边界位置知识的误差或反问题的病态性。在存在噪声或边界建模误差等干扰的情况下，它们有很强的潜力忠实地重建高质量图像。
