iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization

Autores
Blenkmann, Alejandro; Phillips, Holly N.; Princich, Juan P.; Rowe, James B.; Bekinschtein, Tristán A.; Muravchik, Carlos Horacio; Kochen, Silvia
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.
Laboratorio de Electrónica Industrial, Control e Instrumentación (LEICI)
Materia
Ingeniería Electrónica
Electrodos
SEEG, ECoG, intracranial EEG, MRI, CT, atlas, epilepsy
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-nd/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/60927

id SEDICI_dbedcb17f87847c9b5b8b1202693087b
oai_identifier_str oai:sedici.unlp.edu.ar:10915/60927
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode LocalizationBlenkmann, AlejandroPhillips, Holly N.Princich, Juan P.Rowe, James B.Bekinschtein, Tristán A.Muravchik, Carlos HoracioKochen, SilviaIngeniería ElectrónicaElectrodosSEEG, ECoG, intracranial EEG, MRI, CT, atlas, epilepsyThe localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.Laboratorio de Electrónica Industrial, Control e Instrumentación (LEICI)2017-03-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulovideo/quicktimehttp://sedici.unlp.edu.ar/handle/10915/60927enginfo:eu-repo/semantics/altIdentifier/url/http://journal.frontiersin.org/article/10.3389/fninf.2017.00014/fullinfo:eu-repo/semantics/altIdentifier/issn/1662-5196info:eu-repo/semantics/altIdentifier/doi/10.3389/fninf.2017.00014info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:00:04Zoai:sedici.unlp.edu.ar:10915/60927Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:00:04.263SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization
title iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization
spellingShingle iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization
Blenkmann, Alejandro
Ingeniería Electrónica
Electrodos
SEEG, ECoG, intracranial EEG, MRI, CT, atlas, epilepsy
title_short iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization
title_full iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization
title_fullStr iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization
title_full_unstemmed iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization
title_sort iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization
dc.creator.none.fl_str_mv Blenkmann, Alejandro
Phillips, Holly N.
Princich, Juan P.
Rowe, James B.
Bekinschtein, Tristán A.
Muravchik, Carlos Horacio
Kochen, Silvia
author Blenkmann, Alejandro
author_facet Blenkmann, Alejandro
Phillips, Holly N.
Princich, Juan P.
Rowe, James B.
Bekinschtein, Tristán A.
Muravchik, Carlos Horacio
Kochen, Silvia
author_role author
author2 Phillips, Holly N.
Princich, Juan P.
Rowe, James B.
Bekinschtein, Tristán A.
Muravchik, Carlos Horacio
Kochen, Silvia
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Ingeniería Electrónica
Electrodos
SEEG, ECoG, intracranial EEG, MRI, CT, atlas, epilepsy
topic Ingeniería Electrónica
Electrodos
SEEG, ECoG, intracranial EEG, MRI, CT, atlas, epilepsy
dc.description.none.fl_txt_mv The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.
Laboratorio de Electrónica Industrial, Control e Instrumentación (LEICI)
description The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.
publishDate 2017
dc.date.none.fl_str_mv 2017-03-02
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/10915/60927
url http://sedici.unlp.edu.ar/handle/10915/60927
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.frontiersin.org/article/10.3389/fninf.2017.00014/full
info:eu-repo/semantics/altIdentifier/issn/1662-5196
info:eu-repo/semantics/altIdentifier/doi/10.3389/fninf.2017.00014
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
dc.format.none.fl_str_mv video/quicktime
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
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
_version_ 1846064049746345984
score 13.22299