A Review of Algorithms and Hardware Implementations in Electrical Impedance Tomography (Invited)
In recent years, electrical impedance tomography (EIT) has attracted intensive interests due to its noninvasive, ionizing radiation-free, and low-cost advantages, which is promising for both biomedical imaging and industry nondestructive tests. The purpose of this paper is to review state-of-the-art methods including both algorithms and hardwares in EIT. More specifically, for the advanced reconstruction algorithms in mainstream, we offer some insights on classification and comparison. As for the measurement equipment, the structure, configuration modes, and typical systems are reviewed. Furthermore, we discuss the limitations and challenges in EIT technique, such as low-spatial resolution and nonlinear-inversion problems, where future directions, such as solving EIT problems with deep learning, have also been addressed.