Advances in Electrical Impedance Tomography Inverse Problem Solution Methods: From Traditional Regularization to Deep Learning

• Published in: IEEE access Vol. 12; pp. 47797 - 47829
• Main Authors: Dimas, Christos, Alimisis, Vassilis, Uzunoglu, Nikolaos, Sotiriadis, Paul P.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bayes methods; Bayesianism; Biomedical monitoring; Cardiovascular diseases; Conductivity; Deep learning; Electrical impedance; Electrical impedance tomography; Electrodes; Ill-posedness; Image reconstruction; Imaging; inverse problem; Inverse problems; Ionizing radiation; Lung cancer; Machine learning; Medical imaging; Monitoring; Neuroimaging; Pediatrics; Pulmonary diseases; Radiation; Regularization; Temporal resolution; Tomography; Voltage measurement

Electrical Impedance Tomography (EIT) has emerged as a valuable medical imaging modality, which visualizes the conductivity distribution of a subject by performing multi-electrode impedance measurements. EIT finds applications in monitoring lung and cardiac function, brain imaging and the detection...