Clasificación morfológica de eritrocitos en imágenes digitales de frotis de sangre periférica mediante deep learning

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dc.contributor.advisorNarváez Semanate, José Luisspa
dc.contributor.authorMena Quintero, María Camilaspa
dc.coverage.spatialColombia (Popayán, Cauca )spa
dc.creator.cedula20561713428spa
dc.date.accessioned2022-02-21T20:52:36Z
dc.date.available2022-02-21T20:52:36Z
dc.date.issued2022-01-27spa
dc.description.abstractn hematology, the hemogram is one of the evaluative tests used with greater regularity in medical practice, since it allows to evaluate and quantify the different types of cells present in the blood. However, not all characteristics of blood cells can be detailed with this test, which is why a microscopic inspection of the peripheral blood smear is required. The manual exploration of the blood smear, allows to extract, among others, qualitative information about the blood cells, by means of a visual inspection with the help of the microscope; The inspection is a detailed and orderly process, which is carried out with the aim of looking for morphological changes that make it possible to establish differences between normality and abnormality. Since it is carried out manually, the results of this type of classification, based on qualitative parameters; they depend on the skill and experience of the evaluator, which can lead to mistakes, time and money. Taking into account the aforementioned, an erythrocyte classification method was implemented in Matlab, based on morphological descriptors (diameter, perimeter, area, solidity, circularity and concavity), from which a neural network was trained, from which a percentage of accuracy of 83.3% is obtained.eng
dc.description.abstractEn hematología, el hemograma es una de las pruebas valorativas empleadas con mayor regularidad en la praxis médica, ya que permite evaluar y cuantificar los diferentes tipos de células presentes en la sangre. Sin embargo, no todas las características de las células sanguíneas pueden detallarse con esta prueba, razón por la cual, se requiere realizar una inspección microscópica del extendido de sangre periférica. La exploración manual del frotis de sangre, permite extraer entre otros, información cualitativa acerca de las células sanguíneas, por medio de una inspección visual con ayuda del microscopio; la inspección es un proceso detallado y ordenado, que se realiza con el objetivo de buscar cambios morfológicos que permitan establecer diferencias entre normalidad y anormalidad. Dado que se realiza de manera manual, los resultados de este tipo de clasificación, basada en parámetros cualitativos; dependen de la habilidad y experiencia del evaluador, lo que puede implicar errores, gasto de tiempo y dinero. Teniendo en cuenta lo mencionado, se implementó en Matlab un método de clasificación eritrocitaria, basado en descriptores morfológicos (diámetro, perímetro, área, solidez, circularidad y concavidad), a partir de los cuales se entrenó una red neuronal, a partir de la cual se obtiene un porcentaje de exactitud del 83.3%.spa
dc.description.degreelevelPregradospa
dc.description.degreenameIngeniero(a) Biomédico(a)spa
dc.description.degreetypeMonografíaspa
dc.description.notesPresencialspa
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dc.identifier.instnameinstname:Universidad Antonio Nariñospa
dc.identifier.reponamereponame:Repositorio Institucional UANspa
dc.identifier.repourlrepourl:https://repositorio.uan.edu.co/spa
dc.identifier.urihttp://repositorio.uan.edu.co/handle/123456789/5972
dc.language.isospaspa
dc.publisherUniversidad Antonio Nariñospa
dc.publisher.campusPopayán - Alto Caucaspa
dc.publisher.facultyFacultad de Ingeniería Mecánica, Electrónica y Biomédicaspa
dc.publisher.programIngeniería Biomédicaspa
dc.rightsAcceso abierto
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa
dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)spa
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subjectMétodo de clasificaciónes_ES
dc.subjectred neuronales_ES
dc.subjectDeep Learninges_ES
dc.subjectclasificación morfológicaes_ES
dc.subject.keywordClassification methodes_ES
dc.subject.keyworderythrocyteses_ES
dc.subject.keywordmorphological classificationes_ES
dc.subject.keywordDeep Learninges_ES
dc.subject.keywordneural networkes_ES
dc.titleClasificación morfológica de eritrocitos en imágenes digitales de frotis de sangre periférica mediante deep learninges_ES
dc.typeTrabajo de grado (Pregrado y/o Especialización)spa
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1fspa
dc.type.coarversionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audienceGeneralspa
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