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Comparative Analysis of Parallel Brain Activity Mapping Algorithms for High Resolution Brain Models

Análisis comparativo de algoritmos en paralelo de mapeo de actividad cerebral para modelos cerebrales de alta resolución

dc.creatorMolina-Machado , Cristhian D.
dc.creatorCuartas , Ernesto
dc.creatorMartínez-Vargas, Juan D.
dc.creatorGiraldo , Eduardo
dc.date2019-09-20
dc.date.accessioned2021-03-18T21:12:28Z
dc.date.available2021-03-18T21:12:28Z
dc.identifierhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1344
dc.identifier10.22430/22565337.1344
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/11800
dc.descriptionThis paper proposes a comparative analysis between regular and parallel versions of FISTA and Tikhonov-like optimizations for solving the EEG brain mapping problem. Such comparison is performed in terms of computational time reduction and estimation error achieved by the parallelized methods. Two brain models (high- and low-resolution) are used to compare the algorithms. As a result, it can be seen that, if the number of parallel processes increases, computational time decreases significantly for all the head models used in this work, without compromising the reconstruction quality. In addition, it can be concluded that the use of a high-resolution head model produces an improvement in any source reconstruction method in terms of spatial resolution.  en-US
dc.descriptionEn este artículo se propone un análisis comparativo entre versiones regulares y en paralelo de métodos de optimización FISTA y Tikhonov, para resolver el problema de mapeo cerebral a partir de EEG. La comparación se realiza en términos de la reducción del tiempo computacional y el error de estimación obtenido por los métodos paralelizados. Dos modelos de cabeza con alta y baja resolución son usados para la comparación de los algoritmos. Como resultado se puede ver que, si el número de procesos en paralelo se incrementa, el tiempo computacional disminuye significativamente para todos los modelos de cabeza, sin comprometer la calidad de la reconstrucción. Adicionalmente, se puede concluir que el uso de un modelo de cabeza de alta resolución resulta en una mejora de cualquier método de reconstrucción en términos de la resolución espacial.es-ES
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dc.languageeng
dc.publisherInstituto Tecnológico Metropolitano (ITM)en-US
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1344/1370
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1344/1435
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1344/1452
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dc.rightsCopyright (c) 2019 TecnoLógicasen-US
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0en-US
dc.sourceTecnoLógicas; Vol. 22 No. 46 (2019); 233-243en-US
dc.sourceTecnoLógicas; Vol. 22 Núm. 46 (2019); 233-243es-ES
dc.source2256-5337
dc.source0123-7799
dc.subjectParallelized Algorithmsen-US
dc.subjectoptimizationen-US
dc.subjectbrain mappingen-US
dc.subjectelectroencephalographyen-US
dc.subjectAlgoritmos Paralelizadoses-ES
dc.subjectoptimizaciónes-ES
dc.subjectmapeo cerebrales-ES
dc.subjectelectroencefalografíaes-ES
dc.titleComparative Analysis of Parallel Brain Activity Mapping Algorithms for High Resolution Brain Modelsen-US
dc.titleAnálisis comparativo de algoritmos en paralelo de mapeo de actividad cerebral para modelos cerebrales de alta resoluciónes-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeResearch Papersen-US
dc.typeArtículos de investigaciónes-ES


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