Home > Research > Publications & Outputs > Image reconstruction in 3D magnetic induction t...
View graph of relations

Image reconstruction in 3D magnetic induction tomography using a FEM forward model.

Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

Published

Standard

Image reconstruction in 3D magnetic induction tomography using a FEM forward model. / Soleimani, M.; Lionheart, W. R. B.; Peyton, A. J. et al.

2003. Paper presented at 3rd World Congress on Industrial Process Tomography, Banff, Canada.

Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

Harvard

Soleimani, M, Lionheart, WRB, Peyton, AJ & Ma, X 2003, 'Image reconstruction in 3D magnetic induction tomography using a FEM forward model.', Paper presented at 3rd World Congress on Industrial Process Tomography, Banff, Canada, 2/09/03 - 5/09/03. <http://www.vcipt.org/wcipt3.html>

APA

Soleimani, M., Lionheart, W. R. B., Peyton, A. J., & Ma, X. (2003). Image reconstruction in 3D magnetic induction tomography using a FEM forward model.. Paper presented at 3rd World Congress on Industrial Process Tomography, Banff, Canada. http://www.vcipt.org/wcipt3.html

Vancouver

Soleimani M, Lionheart WRB, Peyton AJ, Ma X. Image reconstruction in 3D magnetic induction tomography using a FEM forward model.. 2003. Paper presented at 3rd World Congress on Industrial Process Tomography, Banff, Canada.

Author

Soleimani, M. ; Lionheart, W. R. B. ; Peyton, A. J. et al. / Image reconstruction in 3D magnetic induction tomography using a FEM forward model. Paper presented at 3rd World Congress on Industrial Process Tomography, Banff, Canada.4 p.

Bibtex

@conference{c91ac05038eb456b812adee76e6be20e,
title = "Image reconstruction in 3D magnetic induction tomography using a FEM forward model.",
abstract = "The inverse problem in 3D eddy current imaging is ill-posed and non-linear. The most commonly used image reconstruction algorithms for electrical imaging are based on a linear approximation (the Jacobian Matrix). We start with an initial conductivity distribution. The forward problem is solved and the predicted voltages compared with the calculated voltages from the Finite Element model. The conductivity is then updated using a regularised inverse of the Jacobian. The process is repeated until the predicted voltages from the finite element method agree with the calculated voltages from the finite element model. In this study we present the validity range of a linear inverse problem based on analysis of the Jacobian matrix.",
keywords = "Image reconstruction, Linear and non-linear inverse problems, Magnetic Induction Tomography, Electromagnetics",
author = "M. Soleimani and Lionheart, {W. R. B.} and Peyton, {A. J.} and X. Ma",
year = "2003",
month = sep,
language = "English",
note = "3rd World Congress on Industrial Process Tomography ; Conference date: 02-09-2003 Through 05-09-2003",

}

RIS

TY - CONF

T1 - Image reconstruction in 3D magnetic induction tomography using a FEM forward model.

AU - Soleimani, M.

AU - Lionheart, W. R. B.

AU - Peyton, A. J.

AU - Ma, X.

PY - 2003/9

Y1 - 2003/9

N2 - The inverse problem in 3D eddy current imaging is ill-posed and non-linear. The most commonly used image reconstruction algorithms for electrical imaging are based on a linear approximation (the Jacobian Matrix). We start with an initial conductivity distribution. The forward problem is solved and the predicted voltages compared with the calculated voltages from the Finite Element model. The conductivity is then updated using a regularised inverse of the Jacobian. The process is repeated until the predicted voltages from the finite element method agree with the calculated voltages from the finite element model. In this study we present the validity range of a linear inverse problem based on analysis of the Jacobian matrix.

AB - The inverse problem in 3D eddy current imaging is ill-posed and non-linear. The most commonly used image reconstruction algorithms for electrical imaging are based on a linear approximation (the Jacobian Matrix). We start with an initial conductivity distribution. The forward problem is solved and the predicted voltages compared with the calculated voltages from the Finite Element model. The conductivity is then updated using a regularised inverse of the Jacobian. The process is repeated until the predicted voltages from the finite element method agree with the calculated voltages from the finite element model. In this study we present the validity range of a linear inverse problem based on analysis of the Jacobian matrix.

KW - Image reconstruction

KW - Linear and non-linear inverse problems

KW - Magnetic Induction Tomography

KW - Electromagnetics

M3 - Conference paper

T2 - 3rd World Congress on Industrial Process Tomography

Y2 - 2 September 2003 through 5 September 2003

ER -