The D-Bar Algorithm Fusing Electrical Impedance Tomography with A Priori Radar Data: A Hands-On Analysis

Electrical impedance tomography (EIT) is an imaging modality that can estimate a visualization of the conductivity distribution inside the human body. However, the spatial resolution of EIT is limited because measurements are sensitive to noise. We investigate a technique to incorporate <i>a p...

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Main Authors: Jöran Rixen, Steffen Leonhardt, Jochen Moll, Duy Hai Nguyen, Chuong Ngo
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Algorithms
Subjects:
Online Access:https://www.mdpi.com/1999-4893/16/1/43
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author Jöran Rixen
Steffen Leonhardt
Jochen Moll
Duy Hai Nguyen
Chuong Ngo
author_facet Jöran Rixen
Steffen Leonhardt
Jochen Moll
Duy Hai Nguyen
Chuong Ngo
author_sort Jöran Rixen
collection DOAJ
description Electrical impedance tomography (EIT) is an imaging modality that can estimate a visualization of the conductivity distribution inside the human body. However, the spatial resolution of EIT is limited because measurements are sensitive to noise. We investigate a technique to incorporate <i>a priori</i> information into the EIT reconstructions of the D-Bar algorithm. Our paper aims to help engineers understand the behavior of the D-Bar algorithm and its implementation. The <i>a priori</i> information is provided by a radar setup and a one-dimensional reconstruction of the radar data. The EIT reconstruction is carried out with a D-Bar algorithm. An intermediate step in the D-Bar algorithm is the scattering transform. The <i>a priori</i> information is added in this exact step to increase the spatial resolution of the reconstruction. As the D-Bar algorithm is widely used in the mathematical community and thus far has limited usage in the engineering domain, we also aim to explain the implementation of the algorithm and give an intuitive understanding where possible. Different parameters of the reconstruction algorithm are analyzed systematically with the help of the GREIT figures of merit. Even a limited one-dimensional <i>a priori</i> information can increase the reconstruction quality considerably. Artifacts from noisy EIT measurements are reduced. However, the selection of the amount of <i>a priori</i> information and the estimation of its value can worsen the reconstruction results again.
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spelling doaj.art-47c8cde1dc404d7582e462be9ea320d72023-11-30T20:51:37ZengMDPI AGAlgorithms1999-48932023-01-011614310.3390/a16010043The D-Bar Algorithm Fusing Electrical Impedance Tomography with A Priori Radar Data: A Hands-On AnalysisJöran Rixen0Steffen Leonhardt1Jochen Moll2Duy Hai Nguyen3Chuong Ngo4Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, 52074 Aachen, GermanyHelmholtz Institute for Biomedical Engineering, RWTH Aachen University, 52074 Aachen, GermanyDepartment of Physics, Goethe University Frankfurt, 60438 Frankfurt, GermanyDepartment of Physics, Goethe University Frankfurt, 60438 Frankfurt, GermanyHelmholtz Institute for Biomedical Engineering, RWTH Aachen University, 52074 Aachen, GermanyElectrical impedance tomography (EIT) is an imaging modality that can estimate a visualization of the conductivity distribution inside the human body. However, the spatial resolution of EIT is limited because measurements are sensitive to noise. We investigate a technique to incorporate <i>a priori</i> information into the EIT reconstructions of the D-Bar algorithm. Our paper aims to help engineers understand the behavior of the D-Bar algorithm and its implementation. The <i>a priori</i> information is provided by a radar setup and a one-dimensional reconstruction of the radar data. The EIT reconstruction is carried out with a D-Bar algorithm. An intermediate step in the D-Bar algorithm is the scattering transform. The <i>a priori</i> information is added in this exact step to increase the spatial resolution of the reconstruction. As the D-Bar algorithm is widely used in the mathematical community and thus far has limited usage in the engineering domain, we also aim to explain the implementation of the algorithm and give an intuitive understanding where possible. Different parameters of the reconstruction algorithm are analyzed systematically with the help of the GREIT figures of merit. Even a limited one-dimensional <i>a priori</i> information can increase the reconstruction quality considerably. Artifacts from noisy EIT measurements are reduced. However, the selection of the amount of <i>a priori</i> information and the estimation of its value can worsen the reconstruction results again.https://www.mdpi.com/1999-4893/16/1/43electrical impedance tomographyD-Barradarfusion
spellingShingle Jöran Rixen
Steffen Leonhardt
Jochen Moll
Duy Hai Nguyen
Chuong Ngo
The D-Bar Algorithm Fusing Electrical Impedance Tomography with A Priori Radar Data: A Hands-On Analysis
Algorithms
electrical impedance tomography
D-Bar
radar
fusion
title The D-Bar Algorithm Fusing Electrical Impedance Tomography with A Priori Radar Data: A Hands-On Analysis
title_full The D-Bar Algorithm Fusing Electrical Impedance Tomography with A Priori Radar Data: A Hands-On Analysis
title_fullStr The D-Bar Algorithm Fusing Electrical Impedance Tomography with A Priori Radar Data: A Hands-On Analysis
title_full_unstemmed The D-Bar Algorithm Fusing Electrical Impedance Tomography with A Priori Radar Data: A Hands-On Analysis
title_short The D-Bar Algorithm Fusing Electrical Impedance Tomography with A Priori Radar Data: A Hands-On Analysis
title_sort d bar algorithm fusing electrical impedance tomography with a priori radar data a hands on analysis
topic electrical impedance tomography
D-Bar
radar
fusion
url https://www.mdpi.com/1999-4893/16/1/43
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