Monotonicity-based electrical impedance tomography for lung imaging

Liangdong Zhou, Bastian Harrach, Jin Keun Seo

Research output: Contribution to journalArticle

7 Citations (Scopus)

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.

Original languageEnglish
Article number045005
JournalInverse Problems
Volume34
Issue number4
DOIs
Publication statusPublished - 2018 Mar 2

Fingerprint

Electrical Impedance Tomography
Acoustic impedance
Lung
Tomography
Monotonicity
Imaging
Imaging techniques
Conductivity
Voltage
Electric potential
Ventilation
Phantom
Experiments
Monotonic
Cardiac
Experiment
Monitoring
Computer simulation
Numerical Simulation
Operator

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Signal Processing
  • Mathematical Physics
  • Computer Science Applications
  • Applied Mathematics

Cite this

Zhou, Liangdong ; Harrach, Bastian ; Seo, Jin Keun. / Monotonicity-based electrical impedance tomography for lung imaging. In: Inverse Problems. 2018 ; Vol. 34, No. 4.
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Monotonicity-based electrical impedance tomography for lung imaging. / Zhou, Liangdong; Harrach, Bastian; Seo, Jin Keun.

In: Inverse Problems, Vol. 34, No. 4, 045005, 02.03.2018.

Research output: Contribution to journalArticle

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