Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning

Detalhes bibliográficos
Autor(a) principal: William Javier Garcia Herrera
Data de Publicação: 2020
Tipo de documento: Tese
Título da fonte: Portal de Dados Abertos da CAPES
Texto Completo: https://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=9926982
id BRCRIS_44f7861c2aa555c76ddc531659cc761b
network_acronym_str CAPES
network_name_str Portal de Dados Abertos da CAPES
dc.title.pt-BR.fl_str_mv Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
title Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
spellingShingle Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
convolutional neural network
rede neural convolucional
William Javier Garcia Herrera
title_short Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
title_full Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
title_fullStr Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
title_full_unstemmed Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
title_sort Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning
topic convolutional neural network
rede neural convolucional
publishDate 2020
format doctoralThesis
url https://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=9926982
author_role author
author William Javier Garcia Herrera
author_facet William Javier Garcia Herrera
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/2959262851860061
dc.contributor.advisor1.fl_str_mv LETICIA RITTNER
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/6540619386101635
dc.contributor.advisor1orcid.por.fl_str_mv https://orcid.org/0000-0001-8182-5554
dc.publisher.none.fl_str_mv UNIVERSIDADE ESTADUAL DE CAMPINAS
publisher.none.fl_str_mv UNIVERSIDADE ESTADUAL DE CAMPINAS
instname_str UNIVERSIDADE ESTADUAL DE CAMPINAS
dc.publisher.program.fl_str_mv ENGENHARIA ELÉTRICA
dc.description.course.none.fl_txt_mv ENGENHARIA ELÉTRICA
reponame_str Portal de Dados Abertos da CAPES
collection Portal de Dados Abertos da CAPES
spelling CAPESPortal de Dados Abertos da CAPESAutomatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learningAutomatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learningAutomatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learningAutomatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learningAutomatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learningAutomatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learningAutomatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learningconvolutional neural network2020doctoralThesishttps://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=9926982authorWilliam Javier Garcia Herrerahttp://lattes.cnpq.br/2959262851860061LETICIA RITTNERhttp://lattes.cnpq.br/6540619386101635https://orcid.org/0000-0001-8182-5554UNIVERSIDADE ESTADUAL DE CAMPINASUNIVERSIDADE ESTADUAL DE CAMPINASUNIVERSIDADE ESTADUAL DE CAMPINASENGENHARIA ELÉTRICAENGENHARIA ELÉTRICAPortal de Dados Abertos da CAPESPortal de Dados Abertos da CAPES
identifier_str_mv Herrera, William Javier Garcia. Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning. 2020. Tese.
dc.identifier.citation.fl_str_mv Herrera, William Javier Garcia. Automatic quality control of corpus callosum segmentations in large population studies: comparing deep and classical learning. 2020. Tese.
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