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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/127570
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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) |
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openAccess |
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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 |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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alira@sedici.unlp.edu.ar |
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