Electrical Capacitance Tomography

Electrical Capacitance Tomography (ECT) is a non-invasive imaging technique that reconstructs the internal permittivity distribution of a volume from capacitance measurements at its boundary, solving an inverse problem. Current research emphasizes improving image reconstruction accuracy and speed, particularly through the application of deep learning architectures such as Convolutional Neural Networks (CNNs), Conditional Generative Adversarial Networks (CGANs), and incorporating techniques like neural architecture search and data augmentation. These advancements are enabling higher-resolution imaging at both macroscopic and microscopic scales, with applications ranging from industrial process monitoring to biomedical imaging, significantly impacting fields requiring non-destructive internal visualization.