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Model Selection Based Algorithm in Neonatal Chest EIT

Seifnaraghi, N; De Gelidi, S; Kallio, M; Nordebo, S; Suo-palosaari, M; Frerichs, I; Sorantin, E; ... Bayford, R; + view all (2021) Model Selection Based Algorithm in Neonatal Chest EIT. IEEE Transactions on Biomedical Engineering 10.1109/tbme.2021.3053463. (In press). Green open access

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Abstract

This paper presents a new method for selecting a patient specific forward model to compensate for anatomical variations in electrical impedance tomography (EIT) monitoring of neonates. The method uses a combination of shape sensors and absolute reconstruction. It takes advantage of a probabilistic approach which automatically selects the best estimated forward model fit from pre-stored library models. Absolute/static image reconstruction is performed as the core of the posterior probability calculations. The validity and reliability of the algorithm in detecting a suitable model in the presence of measurement noise is studied with simulated and measured data from 11 patients.

Type: Article
Title: Model Selection Based Algorithm in Neonatal Chest EIT
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/tbme.2021.3053463
Publisher version: http://dx.doi.org/10.1109/tbme.2021.3053463
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Tomography, Pediatrics, Electrodes, Imaging, Conductivity, Image reconstruction, Lung
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10121634
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