Monotonicity-based electrical impedance tomography for lung imaging. (2nd March 2018)

• Record Type: Journal Article
• Authors: Zhou, Liangdong; Harrach, Bastian; Seo, Jin Keun
• Is Part Of: Inverse problems. Volume 34:Number 4(2018:Apr.)
• Publication Date: 2018-03-02
• Subjects: electrical impedance tomography -- continuous lung monitoring -- monotonicity -- inverse problem -- monotonicity-based regularization; Inverse problems (Differential equations) -- Periodicals; 515.357
• DOI: 10.1088/1361-6420/aaaf84
• Languages: English
• ISSNs: 0266-5611

Abstract

Abstract: This paper presents a monotonicity-based spatiotemporal conductivity imaging method for continuous regional lung monitoring using electrical impedance tomography (EIT). The EIT data (i.e. the boundary current–voltage data) can be decomposed into pulmonary, cardiac and other parts using their different periodic natures. The time-differential current–voltage operator corresponding to the lung ventilation can be viewed as either semi-positive or semi-negative definite owing to monotonic conductivity changes within the lung regions. We used these monotonicity constraints to improve the quality of lung EIT imaging. We tested the proposed methods in numerical simulations, phantom experiments and human experiments.