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

ETH Zurich
Long Beach VA and University of California
University of North Carolina at Charlotte
Yonsei University

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

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 - 15 May 2017
Externally published	Yes

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Imaging from internal data
Landweber algorithm
Micro-electrical impedance tomography
Multi-frequency measurements
Optimal control

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10.1016/j.jmaa.2017.01.004

Cite this

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title = "Admittivity imaging from multi-frequency micro-electrical impedance tomography",

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.",

keywords = "Imaging from internal data, Landweber algorithm, Micro-electrical impedance tomography, Multi-frequency measurements, Optimal control",

author = "Habib Ammari and Laure Giovangigli and Nguyen, \{Loc Hoang\} and Seo, \{Jin Keun\}",

note = "Publisher Copyright: {\textcopyright} 2017 Elsevier Inc.",

year = "2017",

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doi = "10.1016/j.jmaa.2017.01.004",

language = "English",

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T1 - Admittivity imaging from multi-frequency micro-electrical impedance tomography

AU - Ammari, Habib

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.

KW - Imaging from internal data

KW - Landweber algorithm

KW - Micro-electrical impedance tomography

KW - Multi-frequency measurements

KW - Optimal control

U2 - 10.1016/j.jmaa.2017.01.004

DO - 10.1016/j.jmaa.2017.01.004

M3 - Article

AN - SCOPUS:85009477084

SN - 0022-247X

VL - 449

SP - 1601

EP - 1618

JO - Journal of Mathematical Analysis and Applications

JF - Journal of Mathematical Analysis and Applications

IS - 2

ER -

Admittivity imaging from multi-frequency micro-electrical impedance tomography

Abstract

UN SDGs

Keywords

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