Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform

Autores
Korol, Ana María; Leguto, Alcides José; Rebechi, Juan Pablo; Riquelme, Bibiana Doris; Ponce De León, Patricia; Bortolato, Santiago Andres; Mancilla Canales, Manuel Arturo
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Automatic recognizing of different populations of several millions of red blood cells (RBCs) is a useful tool in Hematology and Clinical Diagnosis. In this work we studied samples of several millions of RBCs: on one hand healthy control RBCs and on the other hand control RBCs incubated with Trichinella spiralis larval parasites. The alteration on the cells membrane with the parasite can be studied with box-counting dimension on both samples. Previously we applied wavelet transform to all the samples in order to improve the results. The procedure to remove noise from an image is based on the decomposition of the observed signal in a set of wavelets and taking threshold values to select the appropriate coefficients through which the signal can be reconstructed. In our work we compared the results obtained when analyzing the raw signals and the ones obtained after applying wavelet transform, and the results were different and more clearly characterized when the signal were treated with wavelet transform. Finally, the present method using wavelet transform is suitable to optimize the characterization of the RBCs damage when incubated with the larval parasites.
Fil: Korol, Ana María. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Leguto, Alcides José. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rebechi, Juan Pablo. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Riquelme, Bibiana Doris. Universidad Nacional de Rosario. Fundación para el Apoyo de las Ciencias Físicas de Rosario; Argentina
Fil: Ponce De León, Patricia. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Bortolato, Santiago Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Mancilla Canales, Manuel Arturo. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Box counting dimension
Wavelet Transform
Red blood cells
Trichinella spiralis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/63884
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/63884
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet TransformKorol, Ana MaríaLeguto, Alcides JoséRebechi, Juan PabloRiquelme, Bibiana DorisPonce De León, PatriciaBortolato, Santiago AndresMancilla Canales, Manuel ArturoBox counting dimensionWavelet TransformRed blood cellsTrichinella spiralishttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1Automatic recognizing of different populations of several millions of red blood cells (RBCs) is a useful tool in Hematology and Clinical Diagnosis. In this work we studied samples of several millions of RBCs: on one hand healthy control RBCs and on the other hand control RBCs incubated with Trichinella spiralis larval parasites. The alteration on the cells membrane with the parasite can be studied with box-counting dimension on both samples. Previously we applied wavelet transform to all the samples in order to improve the results. The procedure to remove noise from an image is based on the decomposition of the observed signal in a set of wavelets and taking threshold values to select the appropriate coefficients through which the signal can be reconstructed. In our work we compared the results obtained when analyzing the raw signals and the ones obtained after applying wavelet transform, and the results were different and more clearly characterized when the signal were treated with wavelet transform. Finally, the present method using wavelet transform is suitable to optimize the characterization of the RBCs damage when incubated with the larval parasites.Fil: Korol, Ana María. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; ArgentinaFil: Leguto, Alcides José. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rebechi, Juan Pablo. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; ArgentinaFil: Riquelme, Bibiana Doris. Universidad Nacional de Rosario. Fundación para el Apoyo de las Ciencias Físicas de Rosario; ArgentinaFil: Ponce De León, Patricia. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; ArgentinaFil: Bortolato, Santiago Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Mancilla Canales, Manuel Arturo. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaAsociación Argentina de Mecánica Computacional2017-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/63884Korol, Ana María; Leguto, Alcides José; Rebechi, Juan Pablo; Riquelme, Bibiana Doris; Ponce De León, Patricia; et al.; Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform ; Asociación Argentina de Mecánica Computacional; Mecánica Computacional; XXXV; 43; 11-2017; 2533-25382591-3522CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://cimec.org.ar/ojs/index.php/mc/article/view/5467info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-29T12:52:09Zoai:ri.conicet.gov.ar:11336/63884instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-29 12:52:09.548CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform
title Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform
spellingShingle Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform
Korol, Ana María
Box counting dimension
Wavelet Transform
Red blood cells
Trichinella spiralis
title_short Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform
title_full Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform
title_fullStr Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform
title_full_unstemmed Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform
title_sort Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform
dc.creator.none.fl_str_mv Korol, Ana María
Leguto, Alcides José
Rebechi, Juan Pablo
Riquelme, Bibiana Doris
Ponce De León, Patricia
Bortolato, Santiago Andres
Mancilla Canales, Manuel Arturo
author Korol, Ana María
author_facet Korol, Ana María
Leguto, Alcides José
Rebechi, Juan Pablo
Riquelme, Bibiana Doris
Ponce De León, Patricia
Bortolato, Santiago Andres
Mancilla Canales, Manuel Arturo
author_role author
author2 Leguto, Alcides José
Rebechi, Juan Pablo
Riquelme, Bibiana Doris
Ponce De León, Patricia
Bortolato, Santiago Andres
Mancilla Canales, Manuel Arturo
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Box counting dimension
Wavelet Transform
Red blood cells
Trichinella spiralis
topic Box counting dimension
Wavelet Transform
Red blood cells
Trichinella spiralis
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Automatic recognizing of different populations of several millions of red blood cells (RBCs) is a useful tool in Hematology and Clinical Diagnosis. In this work we studied samples of several millions of RBCs: on one hand healthy control RBCs and on the other hand control RBCs incubated with Trichinella spiralis larval parasites. The alteration on the cells membrane with the parasite can be studied with box-counting dimension on both samples. Previously we applied wavelet transform to all the samples in order to improve the results. The procedure to remove noise from an image is based on the decomposition of the observed signal in a set of wavelets and taking threshold values to select the appropriate coefficients through which the signal can be reconstructed. In our work we compared the results obtained when analyzing the raw signals and the ones obtained after applying wavelet transform, and the results were different and more clearly characterized when the signal were treated with wavelet transform. Finally, the present method using wavelet transform is suitable to optimize the characterization of the RBCs damage when incubated with the larval parasites.
Fil: Korol, Ana María. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Leguto, Alcides José. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rebechi, Juan Pablo. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Riquelme, Bibiana Doris. Universidad Nacional de Rosario. Fundación para el Apoyo de las Ciencias Físicas de Rosario; Argentina
Fil: Ponce De León, Patricia. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Bortolato, Santiago Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Mancilla Canales, Manuel Arturo. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Automatic recognizing of different populations of several millions of red blood cells (RBCs) is a useful tool in Hematology and Clinical Diagnosis. In this work we studied samples of several millions of RBCs: on one hand healthy control RBCs and on the other hand control RBCs incubated with Trichinella spiralis larval parasites. The alteration on the cells membrane with the parasite can be studied with box-counting dimension on both samples. Previously we applied wavelet transform to all the samples in order to improve the results. The procedure to remove noise from an image is based on the decomposition of the observed signal in a set of wavelets and taking threshold values to select the appropriate coefficients through which the signal can be reconstructed. In our work we compared the results obtained when analyzing the raw signals and the ones obtained after applying wavelet transform, and the results were different and more clearly characterized when the signal were treated with wavelet transform. Finally, the present method using wavelet transform is suitable to optimize the characterization of the RBCs damage when incubated with the larval parasites.
publishDate 2017
dc.date.none.fl_str_mv 2017-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/63884
Korol, Ana María; Leguto, Alcides José; Rebechi, Juan Pablo; Riquelme, Bibiana Doris; Ponce De León, Patricia; et al.; Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform ; Asociación Argentina de Mecánica Computacional; Mecánica Computacional; XXXV; 43; 11-2017; 2533-2538
2591-3522
CONICET Digital
CONICET
url http://hdl.handle.net/11336/63884
identifier_str_mv Korol, Ana María; Leguto, Alcides José; Rebechi, Juan Pablo; Riquelme, Bibiana Doris; Ponce De León, Patricia; et al.; Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform ; Asociación Argentina de Mecánica Computacional; Mecánica Computacional; XXXV; 43; 11-2017; 2533-2538
2591-3522
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://cimec.org.ar/ojs/index.php/mc/article/view/5467
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Asociación Argentina de Mecánica Computacional
publisher.none.fl_str_mv Asociación Argentina de Mecánica Computacional
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.10058

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