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A computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasis

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datacite.rightshttp://purl.org/coar/access_right/c_abf2eng
dc.contributor.authorIsaza-Jaimes, Angélica
dc.contributor.authorBérmudez, Valmore
dc.contributor.authorBravo, Antonio
dc.contributor.authorSierra Castrillo, Jhoalmis
dc.contributor.authorHernández Lalinde, Juan Diego
dc.contributor.authorFossi, Cleiver A.
dc.contributor.authorFlórez, Anderson
dc.contributor.authorRodríguez, Johel E.
dc.date.accessioned2022-03-30T14:12:03Z
dc.date.available2022-03-30T14:12:03Z
dc.date.issued2020
dc.description.abstractThis article reports a three-stage computational approach for the automatic detection of Leishmania protozoan in light microphotograph from bone marrow samples extracted from patients with visceral Leishmaniasis. The first stage corresponds to the pre-processing of the microscopy images, in which initially a low-pass filter or softener was applied to attenuate the undesired information associated with the images and preserve the edges in the objects contained in the images. The pre-processing stage concluded with the applica tion of consistent gradient operators to the smoothed images to emphasise the changes of the intensities associated with the protozoa edges by determining the gradient module. In the second stage, a procedure-oriented to the selection of regions of interest that were candidates to contain parasites in the pre-processed images was developed, based on the intensity analysis associated with a set of intensity profiles selected from the smoothed images. In the final stage, each region of interest containing protozoa was analysed on the gradient module by a technique based on polar maps, to clas sify its content as a parasite of the genus Leishmania or not. The application of the proposed computational approach to a set of samples of patients with Visceral Leishmaniasis generated a recognition parasite percentage of approximately 80%eng
dc.description.abstractEste artículo reporta un enfoque computacional en tres etapas para la detección automática de protozoos del género Leishmania en microfotografías a partir de muestras de médula ósea extraídas de pacientes con Leishmaniasis visceral. La primera etapa correspondió al preprocesamiento de las imágenes de microscopía, en la que inicialmente se aplicó un filtro de paso bajo para atenuar la información no deseada asociada a las imágenes y preservar los bordes en los objetos. La etapa de preprocesamiento concluyó con la aplicación de operadores de gradiente a las imágenes suavizadas para enfatizar los cambios de las intensidades asociadas con los bordes de los protozoos. En la segunda etapa se elaboró un procedimiento orientado a la selección de las regiones de interés candidatas a contener parásitos, sobre la base del análisis de intensidad asociado a un conjunto de perfiles seleccionados a partir de las imágenes suavizadas. En la etapa final, cada región de interés que contenía protozoos fue analizada en el módulo de gradiente mediante una técnica basada en mapas polares de forma de clasificar su contenido como parásito del género Leishmania. La aplicación del enfoque computacional propuesto generó un porcentaje de reconocimiento del parásito de aproximadamente el 80%spa
dc.format.mimetypepdfspa
dc.identifier.doihttp://doi.org/10.5281/zenodo.4426403
dc.identifier.issn26107988
dc.identifier.urihttps://hdl.handle.net/20.500.12442/9491
dc.identifier.urlhttp://saber.ucv.ve/ojs/index.php/rev_aavft/article/view/21140
dc.language.isoengspa
dc.publisherSaber UCV, Universidad Central de Venezuelaspa
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesseng
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceRevista AVFT - Archivos Venezolanos de Farmacología y Terapéuticaspa
dc.sourceVol 39, No 7 (2020)
dc.subjectProtozoaneng
dc.subjectLeishmaniaeng
dc.subjectmicrographicseng
dc.subjectanisotropic diffusioneng
dc.subjectgradient operatoreng
dc.subjectintensity profileseng
dc.subjectProtozoariospa
dc.subjectmicrografíaspa
dc.subjectdifusión anisotrópicaspa
dc.subjectoperador de gradientespa
dc.subjectperfiles de intensidadspa
dc.titleA computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasiseng
dc.title.translatedUn enfoque computacional para la detección de protozoos del género Leishmania en muestras de médula ósea de pacientes con leishmaniasis visceralspa
dc.type.driverinfo:eu-repo/semantics/articleeng
dc.type.spaArtículo científicospa
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