The University of Southampton
University of Southampton Institutional Repository

Convergence issues of non-linear 3D reconstruction in EIT

Convergence issues of non-linear 3D reconstruction in EIT
Convergence issues of non-linear 3D reconstruction in EIT
The convergence of non-linear reconstruction algorithms for Electrical Impedance Tomography (EIT) depends on many factors, such as the noise of the measurement system, the numerical discretization of the object and the starting value of the iterative approximation. We have shown previously that the result can be made independent of the underlying numerical discretization of the object when adaptive mesh refinement methods are used in combination with a logarithmic image smoothness constraint. The non-linear nature of EIT reconstruction and the unavoidable measurement noise, however, cause several differing solutions in the image space to satisfy the conditions for a 'best-fit' conductivity distribution. A verification of the correctness of an obtained image can only be carried out if the true distribution is known. This, however, is not possible when in-vivo measurements are made and hence we need to establish a measure of similarity between the reconstructed result and a simulated object to characterize the algorithmic behaviour for real experiments. By distributing and reconstructing a large number of initial 3D conductivity estimates on a commodity cluster of PCs, we can determine the quality of the final images and correlate the results with the true images within a short time-span. This gives an indication of the quality of image and provides a measure of convergence properties of the tested algorithms. In this paper, we present results from these investigations into the characteristics and efficient reconstruction of the final image and comment on the clinical importance of choice of starting value
efficient non-linear 3D EIT reconstruction algorithm, initial conductivity estimate, final image correlation, quality and convergence, commodity supercomputing
Molinari, Marc
db124af1-8110-4ac5-823b-cc9bdc896432
Blott, Barry H.
fe2ffa1e-8cd2-448f-a172-63285167e05f
Cox, Simon J.
0e62aaed-24ad-4a74-b996-f606e40e5c55
Daniell, Geoffrey J.
82c59eea-5002-4889-8823-2c6e5b3288d3
Molinari, Marc
db124af1-8110-4ac5-823b-cc9bdc896432
Blott, Barry H.
fe2ffa1e-8cd2-448f-a172-63285167e05f
Cox, Simon J.
0e62aaed-24ad-4a74-b996-f606e40e5c55
Daniell, Geoffrey J.
82c59eea-5002-4889-8823-2c6e5b3288d3

Molinari, Marc, Blott, Barry H., Cox, Simon J. and Daniell, Geoffrey J. (2002) Convergence issues of non-linear 3D reconstruction in EIT. First Mummy Range Workshop on Electric Impedance Imaging, Fort Collins, USA. 31 Jul - 06 Aug 2002. 2 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

The convergence of non-linear reconstruction algorithms for Electrical Impedance Tomography (EIT) depends on many factors, such as the noise of the measurement system, the numerical discretization of the object and the starting value of the iterative approximation. We have shown previously that the result can be made independent of the underlying numerical discretization of the object when adaptive mesh refinement methods are used in combination with a logarithmic image smoothness constraint. The non-linear nature of EIT reconstruction and the unavoidable measurement noise, however, cause several differing solutions in the image space to satisfy the conditions for a 'best-fit' conductivity distribution. A verification of the correctness of an obtained image can only be carried out if the true distribution is known. This, however, is not possible when in-vivo measurements are made and hence we need to establish a measure of similarity between the reconstructed result and a simulated object to characterize the algorithmic behaviour for real experiments. By distributing and reconstructing a large number of initial 3D conductivity estimates on a commodity cluster of PCs, we can determine the quality of the final images and correlate the results with the true images within a short time-span. This gives an indication of the quality of image and provides a measure of convergence properties of the tested algorithms. In this paper, we present results from these investigations into the characteristics and efficient reconstruction of the final image and comment on the clinical importance of choice of starting value

Full text not available from this repository.

More information

Published date: August 2002
Venue - Dates: First Mummy Range Workshop on Electric Impedance Imaging, Fort Collins, USA, 2002-07-31 - 2002-08-06
Keywords: efficient non-linear 3D EIT reconstruction algorithm, initial conductivity estimate, final image correlation, quality and convergence, commodity supercomputing

Identifiers

Local EPrints ID: 45811
URI: http://eprints.soton.ac.uk/id/eprint/45811
PURE UUID: 03cd693e-66d2-4a6d-83ce-3ca3a07f6d5c

Catalogue record

Date deposited: 12 Apr 2007
Last modified: 24 Jul 2020 16:34

Export record

Contributors

Author: Marc Molinari
Author: Barry H. Blott
Author: Simon J. Cox
Author: Geoffrey J. Daniell

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×