Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography

Autores
Fernández Corazza, Mariano; Ellenrieder, Nicolás von; Muravchik, Carlos Horacio
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We localize dynamic electrical conductivity changes and reconstruct their time evolution introducing the spatial filtering technique to electrical impedance tomography (EIT). More precisely, we use the unit-noisegain constrained variation of the distortionless-response linearly constrained minimum variance spatial filter. We address the effects of interference and the use of zero gain constraints. The approach is successfully tested in simulated and real tank phantoms. We compute the position error and resolution to compare the localization performance of the proposed method with the one-step Gauss–Newton reconstruction with Laplacian prior.We also study the effects of sensor position errors. Our results show that EIT spatial filtering is useful for localizing conductivity changes of relatively small size and for estimating their time-courses. Some potential dynamic EIT applications such as acute ischemic stroke detection and neuronal activity localization may benefit from the higher resolution of spatial filters as compared to conventional tomographic reconstruction algorithms.
Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales
Comisión de Investigaciones Científicas de la provincia de Buenos Aires
Materia
Ingeniería Electrónica
Electrical impedance tomography
Spatial filtering
Linearly constrained minimum variance spatial filter
Localization of conductivity changes
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/127570

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spelling Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomographyFernández Corazza, MarianoEllenrieder, Nicolás vonMuravchik, Carlos HoracioIngeniería ElectrónicaElectrical impedance tomographySpatial filteringLinearly constrained minimum variance spatial filterLocalization of conductivity changesWe localize dynamic electrical conductivity changes and reconstruct their time evolution introducing the spatial filtering technique to electrical impedance tomography (EIT). More precisely, we use the unit-noisegain constrained variation of the distortionless-response linearly constrained minimum variance spatial filter. We address the effects of interference and the use of zero gain constraints. The approach is successfully tested in simulated and real tank phantoms. We compute the position error and resolution to compare the localization performance of the proposed method with the one-step Gauss–Newton reconstruction with Laplacian prior.We also study the effects of sensor position errors. Our results show that EIT spatial filtering is useful for localizing conductivity changes of relatively small size and for estimating their time-courses. Some potential dynamic EIT applications such as acute ischemic stroke detection and neuronal activity localization may benefit from the higher resolution of spatial filters as compared to conventional tomographic reconstruction algorithms.Instituto de Investigaciones en Electrónica, Control y Procesamiento de SeñalesComisión de Investigaciones Científicas de la provincia de Buenos Aires2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/127570enginfo:eu-repo/semantics/altIdentifier/issn/2040-7947info:eu-repo/semantics/altIdentifier/doi/10.1002/cnm.2703info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:22:44Zoai:sedici.unlp.edu.ar:10915/127570Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:22:44.378SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography
title Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography
spellingShingle Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography
Fernández Corazza, Mariano
Ingeniería Electrónica
Electrical impedance tomography
Spatial filtering
Linearly constrained minimum variance spatial filter
Localization of conductivity changes
title_short Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography
title_full Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography
title_fullStr Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography
title_full_unstemmed Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography
title_sort Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography
dc.creator.none.fl_str_mv Fernández Corazza, Mariano
Ellenrieder, Nicolás von
Muravchik, Carlos Horacio
author Fernández Corazza, Mariano
author_facet Fernández Corazza, Mariano
Ellenrieder, Nicolás von
Muravchik, Carlos Horacio
author_role author
author2 Ellenrieder, Nicolás von
Muravchik, Carlos Horacio
author2_role author
author
dc.subject.none.fl_str_mv Ingeniería Electrónica
Electrical impedance tomography
Spatial filtering
Linearly constrained minimum variance spatial filter
Localization of conductivity changes
topic Ingeniería Electrónica
Electrical impedance tomography
Spatial filtering
Linearly constrained minimum variance spatial filter
Localization of conductivity changes
dc.description.none.fl_txt_mv We localize dynamic electrical conductivity changes and reconstruct their time evolution introducing the spatial filtering technique to electrical impedance tomography (EIT). More precisely, we use the unit-noisegain constrained variation of the distortionless-response linearly constrained minimum variance spatial filter. We address the effects of interference and the use of zero gain constraints. The approach is successfully tested in simulated and real tank phantoms. We compute the position error and resolution to compare the localization performance of the proposed method with the one-step Gauss–Newton reconstruction with Laplacian prior.We also study the effects of sensor position errors. Our results show that EIT spatial filtering is useful for localizing conductivity changes of relatively small size and for estimating their time-courses. Some potential dynamic EIT applications such as acute ischemic stroke detection and neuronal activity localization may benefit from the higher resolution of spatial filters as compared to conventional tomographic reconstruction algorithms.
Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales
Comisión de Investigaciones Científicas de la provincia de Buenos Aires
description We localize dynamic electrical conductivity changes and reconstruct their time evolution introducing the spatial filtering technique to electrical impedance tomography (EIT). More precisely, we use the unit-noisegain constrained variation of the distortionless-response linearly constrained minimum variance spatial filter. We address the effects of interference and the use of zero gain constraints. The approach is successfully tested in simulated and real tank phantoms. We compute the position error and resolution to compare the localization performance of the proposed method with the one-step Gauss–Newton reconstruction with Laplacian prior.We also study the effects of sensor position errors. Our results show that EIT spatial filtering is useful for localizing conductivity changes of relatively small size and for estimating their time-courses. Some potential dynamic EIT applications such as acute ischemic stroke detection and neuronal activity localization may benefit from the higher resolution of spatial filters as compared to conventional tomographic reconstruction algorithms.
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/127570
url http://sedici.unlp.edu.ar/handle/10915/127570
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/2040-7947
info:eu-repo/semantics/altIdentifier/doi/10.1002/cnm.2703
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
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instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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