Box counting dimension of red blood cells samples when filtered with wavelet transform

Autores
Korol, Ana M.; Leguto, Alcides J.; Rebechi, Juan P.; Riquelme, Bibiana; Ponce de León, Patricia; Bortolato, Santiago; Mancilla Canales, Manuel
Año de publicación
2017
Idioma
español castellano
Tipo de recurso
documento de conferencia
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.
Publicado en: Mecánica Computacional vol. XXXV, no. 43
Facultad de Ingeniería
Materia
Ingeniería
Box counting dimension
Wavelet Transform
Red blood cells
Trichinella spiralis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/105822
Acceder
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network_name_str SEDICI (UNLP)
spelling Box counting dimension of red blood cells samples when filtered with wavelet transformKorol, Ana M.Leguto, Alcides J.Rebechi, Juan P.Riquelme, BibianaPonce de León, PatriciaBortolato, SantiagoMancilla Canales, ManuelIngenieríaBox counting dimensionWavelet TransformRed blood cellsTrichinella spiralisAutomatic 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.Publicado en: <i>Mecánica Computacional</i> vol. XXXV, no. 43Facultad de Ingeniería2017-11info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf2533-2538http://sedici.unlp.edu.ar/handle/10915/105822spainfo:eu-repo/semantics/altIdentifier/url/https://cimec.org.ar/ojs/index.php/mc/article/view/5467info:eu-repo/semantics/altIdentifier/issn/2591-3522info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:23:41Zoai:sedici.unlp.edu.ar:10915/105822Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:23:42.305SEDICI (UNLP) - Universidad Nacional de La Platafalse
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 M.
Ingeniería
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 M.
Leguto, Alcides J.
Rebechi, Juan P.
Riquelme, Bibiana
Ponce de León, Patricia
Bortolato, Santiago
Mancilla Canales, Manuel
author Korol, Ana M.
author_facet Korol, Ana M.
Leguto, Alcides J.
Rebechi, Juan P.
Riquelme, Bibiana
Ponce de León, Patricia
Bortolato, Santiago
Mancilla Canales, Manuel
author_role author
author2 Leguto, Alcides J.
Rebechi, Juan P.
Riquelme, Bibiana
Ponce de León, Patricia
Bortolato, Santiago
Mancilla Canales, Manuel
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Ingeniería
Box counting dimension
Wavelet Transform
Red blood cells
Trichinella spiralis
topic Ingeniería
Box counting dimension
Wavelet Transform
Red blood cells
Trichinella spiralis
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.
Publicado en: <i>Mecánica Computacional</i> vol. XXXV, no. 43
Facultad de Ingeniería
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/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/105822
url http://sedici.unlp.edu.ar/handle/10915/105822
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://cimec.org.ar/ojs/index.php/mc/article/view/5467
info:eu-repo/semantics/altIdentifier/issn/2591-3522
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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