Abstract
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.
Highlights
Electrical impedance tomography (EIT) is an innovative imaging tool widely employed among the scientific community over the last decades
The objective is to highlight tools developed over the past decades that can improve the robustness of EIT, and enable or contribute to the achievement of high-performance imaging even with significant modelling errors or constraints
This review aims at describing works that may potentially contribute to improve static reconstruction performances
Summary
Electrical impedance tomography (EIT) is an innovative imaging tool widely employed among the scientific community over the last decades. EIT is constantly advancing, its use is often confined to applications exhibiting certain simplifying assumptions These assumptions can be a two-dimensional representation, a restriction to a bounded domain or even cases where electrode positions can be known with a good precision and where they can be regularly distributed. The objective is to highlight tools developed over the past decades that can improve the robustness of EIT, and enable or contribute to the achievement of high-performance imaging even with significant modelling errors or constraints. It is organized as follows: first, the usual resolution tools are briefly presented They aim to provide an understanding of how EIT is commonly performed. The last section concludes on the state of the art for robust EIT and gives perspectives
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