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).
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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 |
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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-pp.ucl.ac.uk/id/eprint/10121634 |
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