Detection of cancer in animal tissues: a wavelet approach

Detalhes bibliográficos
Autor(a) principal: Sáfadi, Thelma
Data de Publicação: 2022
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/50848
Resumo: Considering that the biospeckle laser is a dynamic interferometric phenomenon adopted as a tool to monitor changes in biological samples and that the temporal variation of speckle pattern depend on the activity level of the sample surface illuminated, this work proposes to analyse the time-varying scale-mixing matrix. Using two-dimensional scale-mixing wavelet transform several descriptive summaries varying on time are derived. These descriptors are signature of image regularity and fractality useful in tissue classification. In this work we propose to verify the behavior of the energy-flux between the scales, considering a set of 128 images to classifying cancer areas in images of an anaplastic mammary carcinoma in a female canine and in images of skin cancer in a cat obtained over time. The time-varying spectral slopes applied in the analysis of dissimilarities of tissues allowed to note that healthy area descriptors have lower values than cancer area descriptors, resulting in higher Hurst exponents. By using scaling properties of tissue images, we have captured information contained in the background tissue of images which is not utilized when only considering traditional morphological analysis.
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spelling Detection of cancer in animal tissues: a wavelet approachAnimal carcinoma tissuesHurst exponentImage analysisMultiscale analysisNon-decimated wavelet transformConsidering that the biospeckle laser is a dynamic interferometric phenomenon adopted as a tool to monitor changes in biological samples and that the temporal variation of speckle pattern depend on the activity level of the sample surface illuminated, this work proposes to analyse the time-varying scale-mixing matrix. Using two-dimensional scale-mixing wavelet transform several descriptive summaries varying on time are derived. These descriptors are signature of image regularity and fractality useful in tissue classification. In this work we propose to verify the behavior of the energy-flux between the scales, considering a set of 128 images to classifying cancer areas in images of an anaplastic mammary carcinoma in a female canine and in images of skin cancer in a cat obtained over time. The time-varying spectral slopes applied in the analysis of dissimilarities of tissues allowed to note that healthy area descriptors have lower values than cancer area descriptors, resulting in higher Hurst exponents. By using scaling properties of tissue images, we have captured information contained in the background tissue of images which is not utilized when only considering traditional morphological analysis.Universidade Federal de Lavras2022-08-04T22:28:28Z2022-08-04T22:28:28Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfSÁFADI, T. Detection of cancer in animal tissues: a wavelet approach. Brazilian Journal of Biometrics, Lavras, v. 40, n. 1, p. 120-137, 2022. DOI: 10.28951/bjb.v40i1.557.http://repositorio.ufla.br/jspui/handle/1/50848Brazilian Journal of Biometricsreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessSáfadi, Thelmaeng2023-05-19T18:51:12Zoai:localhost:1/50848Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-19T18:51:12Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Detection of cancer in animal tissues: a wavelet approach
title Detection of cancer in animal tissues: a wavelet approach
spellingShingle Detection of cancer in animal tissues: a wavelet approach
Sáfadi, Thelma
Animal carcinoma tissues
Hurst exponent
Image analysis
Multiscale analysis
Non-decimated wavelet transform
title_short Detection of cancer in animal tissues: a wavelet approach
title_full Detection of cancer in animal tissues: a wavelet approach
title_fullStr Detection of cancer in animal tissues: a wavelet approach
title_full_unstemmed Detection of cancer in animal tissues: a wavelet approach
title_sort Detection of cancer in animal tissues: a wavelet approach
author Sáfadi, Thelma
author_facet Sáfadi, Thelma
author_role author
dc.contributor.author.fl_str_mv Sáfadi, Thelma
dc.subject.por.fl_str_mv Animal carcinoma tissues
Hurst exponent
Image analysis
Multiscale analysis
Non-decimated wavelet transform
topic Animal carcinoma tissues
Hurst exponent
Image analysis
Multiscale analysis
Non-decimated wavelet transform
description Considering that the biospeckle laser is a dynamic interferometric phenomenon adopted as a tool to monitor changes in biological samples and that the temporal variation of speckle pattern depend on the activity level of the sample surface illuminated, this work proposes to analyse the time-varying scale-mixing matrix. Using two-dimensional scale-mixing wavelet transform several descriptive summaries varying on time are derived. These descriptors are signature of image regularity and fractality useful in tissue classification. In this work we propose to verify the behavior of the energy-flux between the scales, considering a set of 128 images to classifying cancer areas in images of an anaplastic mammary carcinoma in a female canine and in images of skin cancer in a cat obtained over time. The time-varying spectral slopes applied in the analysis of dissimilarities of tissues allowed to note that healthy area descriptors have lower values than cancer area descriptors, resulting in higher Hurst exponents. By using scaling properties of tissue images, we have captured information contained in the background tissue of images which is not utilized when only considering traditional morphological analysis.
publishDate 2022
dc.date.none.fl_str_mv 2022-08-04T22:28:28Z
2022-08-04T22:28:28Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv SÁFADI, T. Detection of cancer in animal tissues: a wavelet approach. Brazilian Journal of Biometrics, Lavras, v. 40, n. 1, p. 120-137, 2022. DOI: 10.28951/bjb.v40i1.557.
http://repositorio.ufla.br/jspui/handle/1/50848
identifier_str_mv SÁFADI, T. Detection of cancer in animal tissues: a wavelet approach. Brazilian Journal of Biometrics, Lavras, v. 40, n. 1, p. 120-137, 2022. DOI: 10.28951/bjb.v40i1.557.
url http://repositorio.ufla.br/jspui/handle/1/50848
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras
publisher.none.fl_str_mv Universidade Federal de Lavras
dc.source.none.fl_str_mv Brazilian Journal of Biometrics
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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