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A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction †

An image reconstruction method is proposed based on Lagrange-Newton method for electrical impedance tomography (EIT) and ultrasound tomography (UT) dual-modality imaging. Since the change in conductivity distribution is usually accompanied with the change in acoustic impedance distribution, the reco...

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Autores principales: Liang, Guanghui, Ren, Shangjie, Zhao, Shu, Dong, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540236/
https://www.ncbi.nlm.nih.gov/pubmed/31035459
http://dx.doi.org/10.3390/s19091966
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author Liang, Guanghui
Ren, Shangjie
Zhao, Shu
Dong, Feng
author_facet Liang, Guanghui
Ren, Shangjie
Zhao, Shu
Dong, Feng
author_sort Liang, Guanghui
collection PubMed
description An image reconstruction method is proposed based on Lagrange-Newton method for electrical impedance tomography (EIT) and ultrasound tomography (UT) dual-modality imaging. Since the change in conductivity distribution is usually accompanied with the change in acoustic impedance distribution, the reconstruction targets of EIT and UT are unified to the conductivity difference using the same mesh model. Some background medium distribution information obtained from ultrasound transmission and reflection measurements can be used to construct a hard constraint about the conductivity difference distribution. Then, the EIT/UT dual-modality inverse problem is constructed by an equality constraint equation, and the Lagrange multiplier method combining Newton-Raphson iteration is used to solve the EIT/UT dual-modality inverse problem. The numerical and experimental results show that the proposed dual-modality image reconstruction method has a better performance than the single-modality EIT method and is more robust to the measurement noise.
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spelling pubmed-65402362019-06-04 A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction † Liang, Guanghui Ren, Shangjie Zhao, Shu Dong, Feng Sensors (Basel) Article An image reconstruction method is proposed based on Lagrange-Newton method for electrical impedance tomography (EIT) and ultrasound tomography (UT) dual-modality imaging. Since the change in conductivity distribution is usually accompanied with the change in acoustic impedance distribution, the reconstruction targets of EIT and UT are unified to the conductivity difference using the same mesh model. Some background medium distribution information obtained from ultrasound transmission and reflection measurements can be used to construct a hard constraint about the conductivity difference distribution. Then, the EIT/UT dual-modality inverse problem is constructed by an equality constraint equation, and the Lagrange multiplier method combining Newton-Raphson iteration is used to solve the EIT/UT dual-modality inverse problem. The numerical and experimental results show that the proposed dual-modality image reconstruction method has a better performance than the single-modality EIT method and is more robust to the measurement noise. MDPI 2019-04-26 /pmc/articles/PMC6540236/ /pubmed/31035459 http://dx.doi.org/10.3390/s19091966 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liang, Guanghui
Ren, Shangjie
Zhao, Shu
Dong, Feng
A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction †
title A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction †
title_full A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction †
title_fullStr A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction †
title_full_unstemmed A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction †
title_short A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction †
title_sort lagrange-newton method for eit/ut dual-modality image reconstruction †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540236/
https://www.ncbi.nlm.nih.gov/pubmed/31035459
http://dx.doi.org/10.3390/s19091966
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