Parallel CT image reconstruction based on GPUs

[EN] In X-ray computed tomography (CT) iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions from a small number of projections. However, in practice, these methods are not widely used due to the high computational cost of their imp...

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Autores: Flores, Liubov Alexandrovna, Vidal-Gimeno, Vicente-Emilio|||0000-0002-2384-7015, Mayo, Patricia|||0000-0002-8403-5221, Ródenas Escribá, Francisco De Asís|||0000-0003-4564-5171, Verdú Martín, Gumersindo Jesús|||0000-0001-5098-080X
Tipo de recurso: artículo
Fecha de publicación:2014
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/50728
Acceso en línea:https://riunet.upv.es/handle/10251/50728
Access Level:acceso abierto
Palabra clave:CT image reconstruction
GPU-based algorithm
CUDA C
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
MATEMATICA APLICADA
INGENIERIA NUCLEAR
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oai_identifier_str oai:riunet.upv.es:10251/50728
network_acronym_str ES
network_name_str España
repository_id_str
spelling Parallel CT image reconstruction based on GPUsFlores, Liubov AlexandrovnaVidal-Gimeno, Vicente-Emilio|||0000-0002-2384-7015Mayo, Patricia|||0000-0002-8403-5221Ródenas Escribá, Francisco De Asís|||0000-0003-4564-5171Verdú Martín, Gumersindo Jesús|||0000-0001-5098-080XCT image reconstructionGPU-based algorithmCUDA CCIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIALMATEMATICA APLICADAINGENIERIA NUCLEAR[EN] In X-ray computed tomography (CT) iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions from a small number of projections. However, in practice, these methods are not widely used due to the high computational cost of their implementation. Nowadays technology provides the possibility to reduce effectively this drawback. It is the goal of this work to develop a fast GPU-based algorithm to reconstruct high quality images from under sampled and noisy projection data.Research supported by ANITRAN Project PROMETEO/2010/039.ElsevierDepartamento de Ingeniería Química y NuclearDepartamento de Sistemas Informáticos y ComputaciónDepartamento de Matemática AplicadaEscuela Técnica Superior de ArquitecturaInstituto Universitario de Matemática Pura y AplicadaEscuela Técnica Superior de Ingeniería IndustrialInstituto Universitario de Seguridad Industrial, Radiofísica y MedioambientalEscuela Técnica Superior de Ingeniería InformáticaGeneralitat ValencianaRepositorio Institucional de la Universitat Politècnica de València Riunet20142014-02-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/50728reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengGeneralitat Valenciana https://doi.org/10.13039/501100003359 PROMETEO%2F2010%2F039 ANITRAN: METODOLOGIA DE ANALISIS DE INCERTIDUMBRES APLICADA A TRANSITORIOS DE PLANTAS NUCLEARESopen accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/507282026-06-13T07:49:27Z
dc.title.none.fl_str_mv Parallel CT image reconstruction based on GPUs
title Parallel CT image reconstruction based on GPUs
spellingShingle Parallel CT image reconstruction based on GPUs
Flores, Liubov Alexandrovna
CT image reconstruction
GPU-based algorithm
CUDA C
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
MATEMATICA APLICADA
INGENIERIA NUCLEAR
title_short Parallel CT image reconstruction based on GPUs
title_full Parallel CT image reconstruction based on GPUs
title_fullStr Parallel CT image reconstruction based on GPUs
title_full_unstemmed Parallel CT image reconstruction based on GPUs
title_sort Parallel CT image reconstruction based on GPUs
dc.creator.none.fl_str_mv Flores, Liubov Alexandrovna
Vidal-Gimeno, Vicente-Emilio|||0000-0002-2384-7015
Mayo, Patricia|||0000-0002-8403-5221
Ródenas Escribá, Francisco De Asís|||0000-0003-4564-5171
Verdú Martín, Gumersindo Jesús|||0000-0001-5098-080X
author Flores, Liubov Alexandrovna
author_facet Flores, Liubov Alexandrovna
Vidal-Gimeno, Vicente-Emilio|||0000-0002-2384-7015
Mayo, Patricia|||0000-0002-8403-5221
Ródenas Escribá, Francisco De Asís|||0000-0003-4564-5171
Verdú Martín, Gumersindo Jesús|||0000-0001-5098-080X
author_role author
author2 Vidal-Gimeno, Vicente-Emilio|||0000-0002-2384-7015
Mayo, Patricia|||0000-0002-8403-5221
Ródenas Escribá, Francisco De Asís|||0000-0003-4564-5171
Verdú Martín, Gumersindo Jesús|||0000-0001-5098-080X
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Departamento de Ingeniería Química y Nuclear
Departamento de Sistemas Informáticos y Computación
Departamento de Matemática Aplicada
Escuela Técnica Superior de Arquitectura
Instituto Universitario de Matemática Pura y Aplicada
Escuela Técnica Superior de Ingeniería Industrial
Instituto Universitario de Seguridad Industrial, Radiofísica y Medioambiental
Escuela Técnica Superior de Ingeniería Informática
Generalitat Valenciana
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv CT image reconstruction
GPU-based algorithm
CUDA C
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
MATEMATICA APLICADA
INGENIERIA NUCLEAR
topic CT image reconstruction
GPU-based algorithm
CUDA C
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
MATEMATICA APLICADA
INGENIERIA NUCLEAR
description [EN] In X-ray computed tomography (CT) iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions from a small number of projections. However, in practice, these methods are not widely used due to the high computational cost of their implementation. Nowadays technology provides the possibility to reduce effectively this drawback. It is the goal of this work to develop a fast GPU-based algorithm to reconstruct high quality images from under sampled and noisy projection data.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-02-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/50728
url https://riunet.upv.es/handle/10251/50728
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Generalitat Valenciana https://doi.org/10.13039/501100003359 PROMETEO%2F2010%2F039 ANITRAN: METODOLOGIA DE ANALISIS DE INCERTIDUMBRES APLICADA A TRANSITORIOS DE PLANTAS NUCLEARES
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869408029939597312
score 15,301603

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