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

This 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 in...

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Autores:: Isaza-Jaimes, Angélica
Bérmudez, Valmore
Bravo, Antonio
Sierra Castrillo, Jhoalmis
Hernández Lalinde, Juan Diego
Fossi, Cleiver A.
Flórez, Anderson
Rodríguez, Johel E.

Tipo de recurso:

Fecha de publicación:: 2020

Institución:: Universidad Simón Bolívar

Repositorio:: Repositorio Digital USB

Idioma:: eng

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dc.title.eng.fl_str_mv	A computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasis
dc.title.translated.spa.fl_str_mv	Un enfoque computacional para la detección de protozoos del género Leishmania en muestras de médula ósea de pacientes con leishmaniasis visceral
title	A computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasis
spellingShingle	A computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasis Protozoan Leishmania micrographics anisotropic diffusion gradient operator intensity profiles Protozoario micrografía difusión anisotrópica operador de gradiente perfiles de intensidad
title_short	A computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasis
title_full	A computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasis
title_fullStr	A computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasis
title_full_unstemmed	A computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasis
title_sort	A computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral Leishmaniasis
dc.creator.fl_str_mv	Isaza-Jaimes, Angélica Bérmudez, Valmore Bravo, Antonio Sierra Castrillo, Jhoalmis Hernández Lalinde, Juan Diego Fossi, Cleiver A. Flórez, Anderson Rodríguez, Johel E.
dc.contributor.author.none.fl_str_mv	Isaza-Jaimes, Angélica Bérmudez, Valmore Bravo, Antonio Sierra Castrillo, Jhoalmis Hernández Lalinde, Juan Diego Fossi, Cleiver A. Flórez, Anderson Rodríguez, Johel E.
dc.subject.eng.fl_str_mv	Protozoan Leishmania micrographics anisotropic diffusion gradient operator intensity profiles
topic	Protozoan Leishmania micrographics anisotropic diffusion gradient operator intensity profiles Protozoario micrografía difusión anisotrópica operador de gradiente perfiles de intensidad
dc.subject.spa.fl_str_mv	Protozoario micrografía difusión anisotrópica operador de gradiente perfiles de intensidad
description	This 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%
publishDate	2020
dc.date.issued.none.fl_str_mv	2020
dc.date.accessioned.none.fl_str_mv	2022-03-30T14:12:03Z
dc.date.available.none.fl_str_mv	2022-03-30T14:12:03Z
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dc.type.spa.spa.fl_str_mv	Artículo científico
dc.identifier.issn.none.fl_str_mv	26107988
dc.identifier.uri.none.fl_str_mv	https://hdl.handle.net/20.500.12442/9491
dc.identifier.doi.none.fl_str_mv	http://doi.org/10.5281/zenodo.4426403
dc.identifier.url.none.fl_str_mv	http://saber.ucv.ve/ojs/index.php/rev_aavft/article/view/21140
identifier_str_mv	26107988
url	https://hdl.handle.net/20.500.12442/9491 http://doi.org/10.5281/zenodo.4426403 http://saber.ucv.ve/ojs/index.php/rev_aavft/article/view/21140
dc.language.iso.spa.fl_str_mv	eng
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dc.format.mimetype.spa.fl_str_mv	pdf
dc.publisher.spa.fl_str_mv	Saber UCV, Universidad Central de Venezuela
dc.source.spa.fl_str_mv	Revista AVFT - Archivos Venezolanos de Farmacología y Terapéutica
dc.source.none.fl_str_mv	Vol 39, No 7 (2020)
institution	Universidad Simón Bolívar
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spelling	Isaza-Jaimes, Angélica8231ab3d-a8c4-479a-98e7-0bb1f01d8f81Bérmudez, Valmorec2bdde90-7859-4499-94a9-cdae3e689d08Bravo, Antonio07aba3dd-3344-4237-9ad4-3d40d655e915Sierra Castrillo, Jhoalmisb428e633-f0b7-4511-8e99-8c7c2f6fe31bHernández Lalinde, Juan Diego9cdd9c70-b0b1-4267-94ce-ad4d3b00b5e0Fossi, Cleiver A.9c86b495-db48-4aa1-8627-7234014c19d9Flórez, Andersoneeff7a0b-eef1-415e-a084-10c736cdaa19Rodríguez, Johel E.b387eb8f-a5e2-4038-820b-c6d4c9f62a9d2022-03-30T14:12:03Z2022-03-30T14:12:03Z202026107988https://hdl.handle.net/20.500.12442/9491http://doi.org/10.5281/zenodo.4426403http://saber.ucv.ve/ojs/index.php/rev_aavft/article/view/21140This 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%Este 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%pdfengSaber UCV, Universidad Central de VenezuelaAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Revista AVFT - Archivos Venezolanos de Farmacología y TerapéuticaVol 39, No 7 (2020)ProtozoanLeishmaniamicrographicsanisotropic diffusiongradient operatorintensity profilesProtozoariomicrografíadifusión anisotrópicaoperador de gradienteperfiles de intensidadA computational approach for Leishmania genus protozoa detection in bone marrow samples from patients with visceral LeishmaniasisUn enfoque computacional para la detección de protozoos del género Leishmania en muestras de médula ósea de pacientes con leishmaniasis visceralinfo:eu-repo/semantics/articleArtículo científicohttp://purl.org/coar/resource_type/c_2df8fbb1Navarro-Pérez JJ, Pastor-Seller E. 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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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