CT and MRI image fusion based on variance and pixel significance
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista de Engenharia Química e Química |
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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Revista de Engenharia Química e Química |
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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:Revista de Engenharia Química e Químicainstname: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/indexONGhttps://periodicos.ufv.br/jcec/oaijcec.journal@ufv.br||req2@ufv.br2446-94162446-9416opendoar:2023-11-26T15:36:25Revista de Engenharia Química e Química - 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:Revista de Engenharia Química e Química instname:Universidade Federal de Viçosa (UFV) instacron:UFV |
instname_str |
Universidade Federal de Viçosa (UFV) |
instacron_str |
UFV |
institution |
UFV |
reponame_str |
Revista de Engenharia Química e Química |
collection |
Revista de Engenharia Química e Química |
repository.name.fl_str_mv |
Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV) |
repository.mail.fl_str_mv |
jcec.journal@ufv.br||req2@ufv.br |
_version_ |
1800211186763956224 |