CT and MRI image fusion based on variance and pixel significance

Detalhes bibliográficos
Autor(a) principal: Latreche, Boubakeur
Data de Publicação: 2023
Tipo de documento: Artigo
Idioma: eng
Título da fonte: The Journal of Engineering and Exact Sciences
Texto Completo: https://periodicos.ufv.br/jcec/article/view/16619
Resumo: In the medical imaging field, images are obtained using various modalities, including the computed tomography procedure and the magnetic resonance imaging procedure. In which every image contains different information from the other image. For better treatment and diagnosis of a patient, a single composite image must be created by fusing all the pertinent data. This process is known as image fusion. We present an innovative and effective image fusion technique utilizing ILWT and DCT for combining brain-related medical images acquired through there are two steps to this strategy. First, the variance is employed as a contrast evaluation in the DCT domain to combine the approximation coefficients generated by the ILWT decomposition. Second, the coefficients representing the fine details are combined by finding the ideal weighted average based on the importance of the pixels in the ILWT domain. Our method is straightforward, making it simple and suitable for deployment in real-time applications. The experimental results demonstrate our method's outstanding performance with regard to both result quality and in contrast to a number of picture fusion techniques.
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spelling CT and MRI image fusion based on variance and pixel significanceImage fusionmedical imagingILWTDCTIn the medical imaging field, images are obtained using various modalities, including the computed tomography procedure and the magnetic resonance imaging procedure. In which every image contains different information from the other image. For better treatment and diagnosis of a patient, a single composite image must be created by fusing all the pertinent data. This process is known as image fusion. We present an innovative and effective image fusion technique utilizing ILWT and DCT for combining brain-related medical images acquired through there are two steps to this strategy. First, the variance is employed as a contrast evaluation in the DCT domain to combine the approximation coefficients generated by the ILWT decomposition. Second, the coefficients representing the fine details are combined by finding the ideal weighted average based on the importance of the pixels in the ILWT domain. Our method is straightforward, making it simple and suitable for deployment in real-time applications. The experimental results demonstrate our method's outstanding performance with regard to both result quality and in contrast to a number of picture fusion techniques.Universidade Federal de Viçosa - UFV2023-10-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/1661910.18540/jcecvl9iss9pp16619-01eThe Journal of Engineering and Exact Sciences; Vol. 9 No. 9 (2023); 16619-01eThe Journal of Engineering and Exact Sciences; Vol. 9 Núm. 9 (2023); 16619-01eThe Journal of Engineering and Exact Sciences; v. 9 n. 9 (2023); 16619-01e2527-1075reponame:The Journal of Engineering and Exact Sciencesinstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/jcec/article/view/16619/8319Copyright (c) 2023 The Journal of Engineering and Exact Scienceshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessLatreche, Boubakeur2023-11-26T15:36:25Zoai:ojs.periodicos.ufv.br:article/16619Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/oai2527-10752527-1075opendoar:2023-11-26T15:36:25The Journal of Engineering and Exact Sciences - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv CT and MRI image fusion based on variance and pixel significance
title CT and MRI image fusion based on variance and pixel significance
spellingShingle CT and MRI image fusion based on variance and pixel significance
Latreche, Boubakeur
Image fusion
medical imaging
ILWT
DCT
title_short CT and MRI image fusion based on variance and pixel significance
title_full CT and MRI image fusion based on variance and pixel significance
title_fullStr CT and MRI image fusion based on variance and pixel significance
title_full_unstemmed CT and MRI image fusion based on variance and pixel significance
title_sort CT and MRI image fusion based on variance and pixel significance
author Latreche, Boubakeur
author_facet Latreche, Boubakeur
author_role author
dc.contributor.author.fl_str_mv Latreche, Boubakeur
dc.subject.por.fl_str_mv Image fusion
medical imaging
ILWT
DCT
topic Image fusion
medical imaging
ILWT
DCT
description In the medical imaging field, images are obtained using various modalities, including the computed tomography procedure and the magnetic resonance imaging procedure. In which every image contains different information from the other image. For better treatment and diagnosis of a patient, a single composite image must be created by fusing all the pertinent data. This process is known as image fusion. We present an innovative and effective image fusion technique utilizing ILWT and DCT for combining brain-related medical images acquired through there are two steps to this strategy. First, the variance is employed as a contrast evaluation in the DCT domain to combine the approximation coefficients generated by the ILWT decomposition. Second, the coefficients representing the fine details are combined by finding the ideal weighted average based on the importance of the pixels in the ILWT domain. Our method is straightforward, making it simple and suitable for deployment in real-time applications. The experimental results demonstrate our method's outstanding performance with regard to both result quality and in contrast to a number of picture fusion techniques.
publishDate 2023
dc.date.none.fl_str_mv 2023-10-05
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufv.br/jcec/article/view/16619
10.18540/jcecvl9iss9pp16619-01e
url https://periodicos.ufv.br/jcec/article/view/16619
identifier_str_mv 10.18540/jcecvl9iss9pp16619-01e
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufv.br/jcec/article/view/16619/8319
dc.rights.driver.fl_str_mv Copyright (c) 2023 The Journal of Engineering and Exact Sciences
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 The Journal of Engineering and Exact Sciences
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
dc.source.none.fl_str_mv The Journal of Engineering and Exact Sciences; Vol. 9 No. 9 (2023); 16619-01e
The Journal of Engineering and Exact Sciences; Vol. 9 Núm. 9 (2023); 16619-01e
The Journal of Engineering and Exact Sciences; v. 9 n. 9 (2023); 16619-01e
2527-1075
reponame:The Journal of Engineering and Exact Sciences
instname:Universidade Federal de Viçosa (UFV)
instacron:UFV
instname_str Universidade Federal de Viçosa (UFV)
instacron_str UFV
institution UFV
reponame_str The Journal of Engineering and Exact Sciences
collection The Journal of Engineering and Exact Sciences
repository.name.fl_str_mv The Journal of Engineering and Exact Sciences - Universidade Federal de Viçosa (UFV)
repository.mail.fl_str_mv
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