New anisotropic diffusion operator in images filtering

The anisotropic di usion lters have become in the fundamental bases to address the medical images noise problem. The main attributes of these lters are: the noise removal e ectiveness and the preservation of the information belonging to the edges that delimit the objects of an image. Due to these ex...

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Autores:
Vera, M
Gonzalez, E
Huérfano, Y
Gelvez, E
Valbuena, O
Tipo de recurso:
Fecha de publicación:
2020
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
eng
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/5118
Acceso en línea:
https://hdl.handle.net/20.500.12442/5118
https://doi.org/10.1088/1742-6596/1448/1/012019
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network_acronym_str USIMONBOL2
network_name_str Repositorio Digital USB
repository_id_str
dc.title.eng.fl_str_mv New anisotropic diffusion operator in images filtering
title New anisotropic diffusion operator in images filtering
spellingShingle New anisotropic diffusion operator in images filtering
title_short New anisotropic diffusion operator in images filtering
title_full New anisotropic diffusion operator in images filtering
title_fullStr New anisotropic diffusion operator in images filtering
title_full_unstemmed New anisotropic diffusion operator in images filtering
title_sort New anisotropic diffusion operator in images filtering
dc.creator.fl_str_mv Vera, M
Gonzalez, E
Huérfano, Y
Gelvez, E
Valbuena, O
dc.contributor.author.none.fl_str_mv Vera, M
Gonzalez, E
Huérfano, Y
Gelvez, E
Valbuena, O
description The anisotropic di usion lters have become in the fundamental bases to address the medical images noise problem. The main attributes of these lters are: the noise removal e ectiveness and the preservation of the information belonging to the edges that delimit the objects of an image. Due to these excellent attributes, through this article, a comparative study is proposed between a new di usion operator and the Lorentz operator, proposed by the pioneers of anisotropic di usion. For this, a strategy consisting of two phases is designed. In the rst, called operator construction, the composition of functions is used to generate a new di usion operator that meets with the conditions reported for this kind of the mathematical object. In the second phase, denominated ltering, a synthetic cardiac images database, based on computed tomography, is ltered using the aforementioned operators. According with the value obtained for the peak of the signal-to-noise ratio, the new operator shows similar performance to the Lorentz operator. The implementation of this new operator contributes to the generation of new knowledge in digital image processing context.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-04-16T21:50:59Z
dc.date.available.none.fl_str_mv 2020-04-16T21:50:59Z
dc.date.issued.none.fl_str_mv 2020
dc.type.eng.fl_str_mv article
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dc.type.driver.eng.fl_str_mv article
dc.identifier.issn.none.fl_str_mv 17426596
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12442/5118
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1088/1742-6596/1448/1/012019
identifier_str_mv 17426596
url https://hdl.handle.net/20.500.12442/5118
https://doi.org/10.1088/1742-6596/1448/1/012019
dc.language.iso.eng.fl_str_mv eng
language eng
dc.rights.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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dc.format.mimetype.eng.fl_str_mv pdf
dc.publisher.eng.fl_str_mv IOP Publishing
dc.source.eng.fl_str_mv Journal of Physics: Conference Series
Vol. 1448 (2020)
institution Universidad Simón Bolívar
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spelling Vera, M847eada8-99d3-4ff1-a613-ae3f62c30f9eGonzalez, E97bf84f5-3054-4ece-9ee6-9ddf43556fc0Huérfano, Y001cc35e-75ac-48b8-9fd0-3c22464ff80fGelvez, Ed34b29f4-5323-4e58-83ca-7ae2e85e1ce0Valbuena, O4286f2e0-ce46-49ce-a106-bd00c21a76e92020-04-16T21:50:59Z2020-04-16T21:50:59Z202017426596https://hdl.handle.net/20.500.12442/5118https://doi.org/10.1088/1742-6596/1448/1/012019The anisotropic di usion lters have become in the fundamental bases to address the medical images noise problem. The main attributes of these lters are: the noise removal e ectiveness and the preservation of the information belonging to the edges that delimit the objects of an image. Due to these excellent attributes, through this article, a comparative study is proposed between a new di usion operator and the Lorentz operator, proposed by the pioneers of anisotropic di usion. For this, a strategy consisting of two phases is designed. In the rst, called operator construction, the composition of functions is used to generate a new di usion operator that meets with the conditions reported for this kind of the mathematical object. In the second phase, denominated ltering, a synthetic cardiac images database, based on computed tomography, is ltered using the aforementioned operators. According with the value obtained for the peak of the signal-to-noise ratio, the new operator shows similar performance to the Lorentz operator. The implementation of this new operator contributes to the generation of new knowledge in digital image processing context.pdfengIOP PublishingAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/http://purl.org/coar/access_right/c_abf2Journal of Physics: Conference SeriesVol. 1448 (2020)New anisotropic diffusion operator in images filteringarticlearticlehttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Goldberg R, Smith R, Mottley J and Ferrara W 2000 The Biomedical Engineering Handbook ed J Bronzino (Boca Raton: CRC press) UltrasoundMacovski A, Pauly J, Schenck J, Kwong K, Chesler D, Hu X, Chen W, Patel M, Ugurbil K and Olly S 2000 The Biomedical Engineering Handbook ed J Bronzino (Boca Raton: CRC press) Magnetic resonance imagingReba R 1993 The Journal of the American Medical Association 270 230Fuchs T, Kachelriess M and Kalender W 2000 IEEE Engineering in Medicine and Biology MagazineKalender W 2000 Computed tomography: Fundamentals, system technology, image quality, applications (Germany: Publicis MCD Verlag)Zanella R, Boccacci P, Zanni L and Bertero M 2009 Inverse Problems 25 1Maiera A, Wigstrm L, Hofmann H, Hornegger J, Zhu L, Strobel N and Fahrig R 2011 Medical Physics 38 5896Barrett J and Keat N 2004 Radiographics 24 1679Wang G and Vannier M 1994 Radiology 191 79Perona P and Malik J 1990 IEEE Transaction on Pattern Analysis Machine Intelligence 12 629Avcibas I, Sankur B and Sayood K 2002 Journal of Electronic Imaging 11 206Burden R and Faires D 2010 Numerical analysis (Mexico: Cengage Learning)Vera M 2014 Segmentación de estructuras cardiacas en imágenes de tomografía computarizada multi-corte (Venezuela: Universidad de Los Andes)Pulido D 2014 Sobre el modelo de difusión anisotrópica de Perona-Malik (Colombia: Universidad Nacional de Colombia)ORIGINALPDF.pdfPDF.pdfPDFapplication/pdf755080https://bonga.unisimon.edu.co/bitstreams/5dd8461f-a37f-4d58-ad52-911738be805f/download01d727d5d63d0dba65d3ab5d1f3f28deMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://bonga.unisimon.edu.co/bitstreams/0c176d41-898c-4f5d-b952-7343d58f679d/download4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-8381https://bonga.unisimon.edu.co/bitstreams/4f096dc4-61df-4a0b-8291-cce96c2af227/download733bec43a0bf5ade4d97db708e29b185MD53TEXTNew_anisotropic_diffusion_operator_images-filtering.pdf.txtNew_anisotropic_diffusion_operator_images-filtering.pdf.txtExtracted texttext/plain19611https://bonga.unisimon.edu.co/bitstreams/6a0d17b4-4856-4329-9c57-316df229e2c6/download48a862f644a5294153441c36ead51554MD54PDF.pdf.txtPDF.pdf.txtExtracted texttext/plain20135https://bonga.unisimon.edu.co/bitstreams/a9bd143c-e111-4c92-a3cc-dae89202f949/download54188976a26167d137e0f8a67ebb0f84MD56THUMBNAILNew_anisotropic_diffusion_operator_images-filtering.pdf.jpgNew_anisotropic_diffusion_operator_images-filtering.pdf.jpgGenerated Thumbnailimage/jpeg1382https://bonga.unisimon.edu.co/bitstreams/e9cb22c9-3cc8-4be6-a105-28baccb72edb/download11bd4defba06cf3cd093fd5fafbb8141MD55PDF.pdf.jpgPDF.pdf.jpgGenerated Thumbnailimage/jpeg3542https://bonga.unisimon.edu.co/bitstreams/a9bad5fa-9306-43c7-b098-a1da990e16b9/download520567a40e1aaef52f93474cf352c65eMD5720.500.12442/5118oai:bonga.unisimon.edu.co:20.500.12442/51182024-08-14 21:52:57.946http://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internacionalopen.accesshttps://bonga.unisimon.edu.coRepositorio Digital Universidad Simón Bolívarrepositorio.digital@unisimon.edu.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