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dc.date.accessioned 2017-06-29T12:48:59Z
dc.date.available 2017-06-29T12:48:59Z
dc.date.issued 2017-03-02
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/60927
dc.description.abstract 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. en
dc.language en es
dc.subject Electrodos es
dc.subject SEEG, ECoG, intracranial EEG, MRI, CT, atlas, epilepsy en
dc.title iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization en
dc.type Articulo es
sedici.identifier.uri http://journal.frontiersin.org/article/10.3389/fninf.2017.00014/full es
sedici.identifier.other https://doi.org/10.3389/fninf.2017.00014
sedici.identifier.issn 1662-5196 es
sedici.creator.person Blenkmann, Alejandro es
sedici.creator.person Phillips, Holly N. es
sedici.creator.person Princich, Juan P. es
sedici.creator.person Rowe, James B. es
sedici.creator.person Bekinschtein, Tristán A. es
sedici.creator.person Muravchik, Carlos Horacio es
sedici.creator.person Kochen, Silvia es
sedici.subject.materias Ingeniería Electrónica es
sedici.description.fulltext true es
mods.originInfo.place Laboratorio de Electrónica Industrial, Control e Instrumentación (LEICI) es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
sedici.description.peerReview peer-review es
sedici.relation.journalTitle Frontiers in NeuroInformatics es
sedici.relation.journalVolumeAndIssue vol. 11, art. 14 es


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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)