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dc.rights.licenseLicencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacionalspa
dc.contributor.authorContreras, Yudith
dc.contributor.authorVera, Miguel
dc.contributor.authorHuérfano, Yoleidy
dc.contributor.authorValbuena, Oscar
dc.contributor.authorSalazar, Williams
dc.contributor.authorVera, María Isabel
dc.contributor.authorBorrero, Maryury
dc.contributor.authorBarrera, Doris
dc.contributor.authorHernández, Carlos
dc.contributor.authorMolina, Ángel Valentín
dc.contributor.authorMartínez, Luis Javier
dc.contributor.authorSáenz, Frank
dc.contributor.authorVivas, Marisela
dc.contributor.authorSalazar, Juan
dc.contributor.authorGelvez, Elkin
dc.date.accessioned2019-01-25T16:23:23Z
dc.date.available2019-01-25T16:23:23Z
dc.date.issued2018
dc.identifier.issn18564550
dc.identifier.urihttp://hdl.handle.net/20.500.12442/2527
dc.description.abstractIn this work an adaptation of the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, in the context of digital medical image processing is proposed. Specifically, synthetic images reported in the literature are used as numerical phantoms. Construction of the synthetic images was inspired by a detailed analysis of some of the imperfections found in the real multilayer cardiac computed tomography images. Of all the imperfections considered, only Poisson noise was selected and incorporated into a synthetic database. An example is presented in which images contaminated with Poisson noise are processed and then subject to two classical digital smoothing techniques, identified as Gaussian filter and anisotropic diffusion filter. Additionally, the peak of the signal-to-noise ratio (PSNR) is considered as a metric to analyze the performance of these filters.eng
dc.language.isoengeng
dc.publisherSociedad Latinoamericana de Hipertensiónspa
dc.sourceRevista Latinoamericana de Hipertensiónspa
dc.sourceVol. 13, No. 4 (2018)spa
dc.source.urihttp://www.revhipertension.com/rlh_4_2018/1_digital_processing_of_medical.pdfeng
dc.subjectCRISP-DM Methodologyeng
dc.subjectSynthetic cardiac imageseng
dc.subjectComputerized tomographyeng
dc.subjectNoiseeng
dc.subjectArtifactseng
dc.titleDigital processing of medical images: application in synthetic cardiac datasets using the CRISP_DM methodologyeng
dc.title.alternativeProcesamiento digital de imágenes médicas: aplicación a bases de datos sintéticas cardiacas usando la metodología CRISP-DMspa
dc.typearticleeng
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccess


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