On the geometric modulation of skin lesion growth: a mathematical model for melanoma

Detalhes bibliográficos
Autor(a) principal: Mendes,Ana Isabel
Data de Publicação: 2016
Outros Autores: Nogueira,Conceição, Pereira,Jorge, Fonseca-Pinto,Rui
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Research on Biomedical Engineering (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402016000100044
Resumo: Abstract Introduction Early detection of suspicious skin lesions is critical to prevent skin malignancies, particularly the melanoma, which is the most dangerous form of human skin cancer. In the last decade, image processing techniques have been an increasingly important tool for early detection and mathematical models play a relevant role in mapping the progression of lesions. Methods This work presents an algorithm to describe the evolution of the border of the skin lesion based on two main measurable markers: the symmetry and the geometric growth path of the lesion. The proposed methodology involves two dermoscopic images of the same melanocytic lesion obtained at different moments in time. By applying a mathematical model based on planar linear transformations, measurable parameters related to symmetry and growth are extracted. Results With this information one may compare the actual evolution in the lesion with the outcomes from the geometric model. First, this method was tested on predefined images whose growth was controlled and the symmetry known which were used for validation. Then the methodology was tested in real dermoscopic melanoma images in which the parameters of the mathematical model revealed symmetry and growth rates consistent with a typical melanoma behavior. Conclusions The method developed proved to show very accurate information about the target growth markers (variation on the growth along the border, the deformation and the symmetry of the lesion trough the time). All the results, validated by the expected phantom outputs, were similar to the ones on the real images.
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spelling On the geometric modulation of skin lesion growth: a mathematical model for melanomaDigital image skin processingMelanomaSegmentationDermoscopyLinear transformationsAbstract Introduction Early detection of suspicious skin lesions is critical to prevent skin malignancies, particularly the melanoma, which is the most dangerous form of human skin cancer. In the last decade, image processing techniques have been an increasingly important tool for early detection and mathematical models play a relevant role in mapping the progression of lesions. Methods This work presents an algorithm to describe the evolution of the border of the skin lesion based on two main measurable markers: the symmetry and the geometric growth path of the lesion. The proposed methodology involves two dermoscopic images of the same melanocytic lesion obtained at different moments in time. By applying a mathematical model based on planar linear transformations, measurable parameters related to symmetry and growth are extracted. Results With this information one may compare the actual evolution in the lesion with the outcomes from the geometric model. First, this method was tested on predefined images whose growth was controlled and the symmetry known which were used for validation. Then the methodology was tested in real dermoscopic melanoma images in which the parameters of the mathematical model revealed symmetry and growth rates consistent with a typical melanoma behavior. Conclusions The method developed proved to show very accurate information about the target growth markers (variation on the growth along the border, the deformation and the symmetry of the lesion trough the time). All the results, validated by the expected phantom outputs, were similar to the ones on the real images.Sociedade Brasileira de Engenharia Biomédica2016-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402016000100044Research on Biomedical Engineering v.32 n.1 2016reponame:Research on Biomedical Engineering (Online)instname:Sociedade Brasileira de Engenharia Biomédica (SBEB)instacron:SBEB10.1590/2446-4740.02815info:eu-repo/semantics/openAccessMendes,Ana IsabelNogueira,ConceiçãoPereira,JorgeFonseca-Pinto,Ruieng2016-04-26T00:00:00Zoai:scielo:S2446-47402016000100044Revistahttp://www.rbejournal.org/https://old.scielo.br/oai/scielo-oai.php||rbe@rbejournal.org2446-47402446-4732opendoar:2016-04-26T00:00Research on Biomedical Engineering (Online) - Sociedade Brasileira de Engenharia Biomédica (SBEB)false
dc.title.none.fl_str_mv On the geometric modulation of skin lesion growth: a mathematical model for melanoma
title On the geometric modulation of skin lesion growth: a mathematical model for melanoma
spellingShingle On the geometric modulation of skin lesion growth: a mathematical model for melanoma
Mendes,Ana Isabel
Digital image skin processing
Melanoma
Segmentation
Dermoscopy
Linear transformations
title_short On the geometric modulation of skin lesion growth: a mathematical model for melanoma
title_full On the geometric modulation of skin lesion growth: a mathematical model for melanoma
title_fullStr On the geometric modulation of skin lesion growth: a mathematical model for melanoma
title_full_unstemmed On the geometric modulation of skin lesion growth: a mathematical model for melanoma
title_sort On the geometric modulation of skin lesion growth: a mathematical model for melanoma
author Mendes,Ana Isabel
author_facet Mendes,Ana Isabel
Nogueira,Conceição
Pereira,Jorge
Fonseca-Pinto,Rui
author_role author
author2 Nogueira,Conceição
Pereira,Jorge
Fonseca-Pinto,Rui
author2_role author
author
author
dc.contributor.author.fl_str_mv Mendes,Ana Isabel
Nogueira,Conceição
Pereira,Jorge
Fonseca-Pinto,Rui
dc.subject.por.fl_str_mv Digital image skin processing
Melanoma
Segmentation
Dermoscopy
Linear transformations
topic Digital image skin processing
Melanoma
Segmentation
Dermoscopy
Linear transformations
description Abstract Introduction Early detection of suspicious skin lesions is critical to prevent skin malignancies, particularly the melanoma, which is the most dangerous form of human skin cancer. In the last decade, image processing techniques have been an increasingly important tool for early detection and mathematical models play a relevant role in mapping the progression of lesions. Methods This work presents an algorithm to describe the evolution of the border of the skin lesion based on two main measurable markers: the symmetry and the geometric growth path of the lesion. The proposed methodology involves two dermoscopic images of the same melanocytic lesion obtained at different moments in time. By applying a mathematical model based on planar linear transformations, measurable parameters related to symmetry and growth are extracted. Results With this information one may compare the actual evolution in the lesion with the outcomes from the geometric model. First, this method was tested on predefined images whose growth was controlled and the symmetry known which were used for validation. Then the methodology was tested in real dermoscopic melanoma images in which the parameters of the mathematical model revealed symmetry and growth rates consistent with a typical melanoma behavior. Conclusions The method developed proved to show very accurate information about the target growth markers (variation on the growth along the border, the deformation and the symmetry of the lesion trough the time). All the results, validated by the expected phantom outputs, were similar to the ones on the real images.
publishDate 2016
dc.date.none.fl_str_mv 2016-03-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2446-47402016000100044
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2446-4740.02815
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Engenharia Biomédica
publisher.none.fl_str_mv Sociedade Brasileira de Engenharia Biomédica
dc.source.none.fl_str_mv Research on Biomedical Engineering v.32 n.1 2016
reponame:Research on Biomedical Engineering (Online)
instname:Sociedade Brasileira de Engenharia Biomédica (SBEB)
instacron:SBEB
instname_str Sociedade Brasileira de Engenharia Biomédica (SBEB)
instacron_str SBEB
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reponame_str Research on Biomedical Engineering (Online)
collection Research on Biomedical Engineering (Online)
repository.name.fl_str_mv Research on Biomedical Engineering (Online) - Sociedade Brasileira de Engenharia Biomédica (SBEB)
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