Admittivity imaging from multi-frequency micro-electrical impedance tomography

Habib Ammari; Laure Giovangigli; Loc Hoang Nguyen; Jin Keun Seo

doi:10.1016/j.jmaa.2017.01.004

Admittivity imaging from multi-frequency micro-electrical impedance tomography

Habib Ammari, Laure Giovangigli, Loc Hoang Nguyen, Jin Keun Seo

Department of Computational Science and Engineering

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

The aim of this paper is to propose an optimal control optimization algorithm for reconstructing admittivity distributions (i.e., both conductivity and permittivity) from multi-frequency micro-electrical impedance tomography. A convergent and stable optimal control scheme is shown to be obtainable from multi-frequency data. This opens a door for convergence analysis of optimal control type approaches in imaging from internal data. The results of this paper have potential applicability in cancer imaging, cell culturing and differentiation, food sciences, and biotechnology.

Original language	English
Pages (from-to)	1601-1618
Number of pages	18
Journal	Journal of Mathematical Analysis and Applications
Volume	449
Issue number	2
DOIs	https://doi.org/10.1016/j.jmaa.2017.01.004
Publication status	Published - 2017 May 15

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Inc.

All Science Journal Classification (ASJC) codes

Analysis
Applied Mathematics

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.jmaa.2017.01.004

Cite this

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abstract = "The aim of this paper is to propose an optimal control optimization algorithm for reconstructing admittivity distributions (i.e., both conductivity and permittivity) from multi-frequency micro-electrical impedance tomography. A convergent and stable optimal control scheme is shown to be obtainable from multi-frequency data. This opens a door for convergence analysis of optimal control type approaches in imaging from internal data. The results of this paper have potential applicability in cancer imaging, cell culturing and differentiation, food sciences, and biotechnology.",

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AU - Giovangigli, Laure

AU - Nguyen, Loc Hoang

AU - Seo, Jin Keun

PY - 2017/5/15

Y1 - 2017/5/15

N2 - The aim of this paper is to propose an optimal control optimization algorithm for reconstructing admittivity distributions (i.e., both conductivity and permittivity) from multi-frequency micro-electrical impedance tomography. A convergent and stable optimal control scheme is shown to be obtainable from multi-frequency data. This opens a door for convergence analysis of optimal control type approaches in imaging from internal data. The results of this paper have potential applicability in cancer imaging, cell culturing and differentiation, food sciences, and biotechnology.

AB - The aim of this paper is to propose an optimal control optimization algorithm for reconstructing admittivity distributions (i.e., both conductivity and permittivity) from multi-frequency micro-electrical impedance tomography. A convergent and stable optimal control scheme is shown to be obtainable from multi-frequency data. This opens a door for convergence analysis of optimal control type approaches in imaging from internal data. The results of this paper have potential applicability in cancer imaging, cell culturing and differentiation, food sciences, and biotechnology.

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Admittivity imaging from multi-frequency micro-electrical impedance tomography

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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