title: GREIT: a unified approach to 2D linear EIT reconstruction of lung images.
abstract: Electrical impedance tomography (EIT) is an attractive method for clinically monitoring patients during mechanical ventilation, because it can provide a non-invasive continuous image of pulmonary impedance which indicates the distribution of ventilation. However, most clinical and physiological research in lung EIT is done using older and proprietary algorithms; this is an obstacle to interpretation of EIT images because the reconstructed images are not well characterized. To address this issue, we develop a consensus linear reconstruction algorithm for lung EIT, called GREIT (Graz consensus Reconstruction algorithm for EIT). This paper describes the unified approach to linear image reconstruction developed for GREIT. The framework for the linear reconstruction algorithm consists of (1) detailed finite element models of a representative adult and neonatal thorax, (2) consensus on the performance figures of merit for EIT image reconstruction and (3) a systematic approach to optimize a linear reconstruction matrix to desired performance measures. Consensus figures of merit, in order of importance, are (a) uniform amplitude response, (b) small and uniform position error, (c) small ringing artefacts, (d) uniform resolution, (e) limited shape deformation and (f) high resolution. Such figures of merit must be attained while maintaining small noise amplification and small sensitivity to electrode and boundary movement. This approach represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring. All software and data to implement and test the algorithm have been made available under an open source license which allows free research and commercial use.
authors.affiliation: Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada.
authors.forename: Andy
authors.initials: A
authors.lastname: Adler
authors.forename: John H
authors.initials: JH
authors.lastname: Arnold
authors.forename: Richard
authors.initials: R
authors.lastname: Bayford
authors.forename: Andrea
authors.initials: A
authors.lastname: Borsic
authors.forename: Brian
authors.initials: B
authors.lastname: Brown
authors.forename: Paul
authors.initials: P
authors.lastname: Dixon
authors.forename: Theo J C
authors.initials: TJ
authors.lastname: Faes
authors.forename: Inéz
authors.initials: I
authors.lastname: Frerichs
authors.forename: Hervé
authors.initials: H
authors.lastname: Gagnon
authors.forename: Yvo
authors.initials: Y
authors.lastname: Gärber
authors.forename: Bartłomiej
authors.initials: B
authors.lastname: Grychtol
authors.forename: Günter
authors.initials: G
authors.lastname: Hahn
authors.forename: William R B
authors.initials: WR
authors.lastname: Lionheart
authors.forename: Anjum
authors.initials: A
authors.lastname: Malik
authors.forename: Robert P
authors.initials: RP
authors.lastname: Patterson
authors.forename: Janet
authors.initials: J
authors.lastname: Stocks
authors.forename: Andrew
authors.initials: A
authors.lastname: Tizzard
authors.forename: Norbert
authors.initials: N
authors.lastname: Weiler
authors.forename: Gerhard K
authors.initials: GK
authors.lastname: Wolf
mesh_terms: D000328:Adult; D000465:Algorithms; D017097:Electric Impedance; D020342:Finite Element Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D007231:Infant, Newborn; D008168:Lung / Q000503:physiopathology*; D008953:Models, Anatomic; D008954:Models, Biological; D008991:Monitoring, Physiologic / Q000379:methods / Q000706:statistics & numerical data; D012121:Respiration, Artificial; D014054:Tomography / Q000379:methods* / Q000706:statistics & numerical data