Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Capítulo de livro |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/B978-0-12-822688-9.00014-1 http://hdl.handle.net/11449/241373 |
Resumo: | Analysis of the atherosclerotic lesions deposited in the carotid artery is so far an essential task for estimating possible cardiovascular disorders in patients. The immediate assessment of such lesion, as well as its morphology and composition, turns out necessary to avoid its progression beforehand, thus preventing more severe conditions such as heart attacks and strokes caused by calcified elements observed in advanced stages. Heretofore, a number of works addressed medical diagnosis problems through computational approaches, developing Computer-Aided Diagnosis (CAD) tools to detect, among several applications, atherosclerotic plaques formed in carotid arteries. In this context, a graph-based machine learning framework called Optimum-Path Forest (OPF) was successfully employed to tackle several CAD-based problems, even though no one still explores the model to classify the task mentioned above. Therefore this paper proposes the classification of regions in atherosclerotic lesions as calcified or noncalcified debris through OPF-based approaches. In the process, handcrafted features are extracted from pixels of computed tomography angiography images of the carotid artery. Also, each pixel is labeled by an expert as a calcified or noncalcified element. Thereafter, the OPF classifier, as well as four variants, namely Fuzzy OPF, OPF. knn, Probabilistic OPF, and the OPF for anomaly detection, are compared for the task of predicting whether the pixel of the carotid artery stands for the calcium of the atherosclerotic lesion or not. © 2022 Copyright |
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Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forestAtherosclerotic lesionsCarotid arteryComputer-aided diagnosisMedical imagesOptimum-path forestAnalysis of the atherosclerotic lesions deposited in the carotid artery is so far an essential task for estimating possible cardiovascular disorders in patients. The immediate assessment of such lesion, as well as its morphology and composition, turns out necessary to avoid its progression beforehand, thus preventing more severe conditions such as heart attacks and strokes caused by calcified elements observed in advanced stages. Heretofore, a number of works addressed medical diagnosis problems through computational approaches, developing Computer-Aided Diagnosis (CAD) tools to detect, among several applications, atherosclerotic plaques formed in carotid arteries. In this context, a graph-based machine learning framework called Optimum-Path Forest (OPF) was successfully employed to tackle several CAD-based problems, even though no one still explores the model to classify the task mentioned above. Therefore this paper proposes the classification of regions in atherosclerotic lesions as calcified or noncalcified debris through OPF-based approaches. In the process, handcrafted features are extracted from pixels of computed tomography angiography images of the carotid artery. Also, each pixel is labeled by an expert as a calcified or noncalcified element. Thereafter, the OPF classifier, as well as four variants, namely Fuzzy OPF, OPF. knn, Probabilistic OPF, and the OPF for anomaly detection, are compared for the task of predicting whether the pixel of the carotid artery stands for the calcium of the atherosclerotic lesion or not. © 2022 CopyrightDepartment of Computing São Paulo State University, BauruDepartment of Computing São Carlos Federal University, São CarlosDepartment of Computing São Paulo State University, BauruUniversidade Estadual Paulista (UNESP)São Carlos Federal UniversityJodas, Danilo Samuel [UNESP]Roder, Mateus [UNESP]Pires, Rafael [UNESP]Silva Santana, Marcos Cleison [UNESP]de Souza, Luis A.Passos, Leandro Aparecido [UNESP]2023-03-01T20:59:04Z2023-03-01T20:59:04Z2022-01-24info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookPart137-154http://dx.doi.org/10.1016/B978-0-12-822688-9.00014-1Optimum-Path Forest: Theory, Algorithms, and Applications, p. 137-154.http://hdl.handle.net/11449/24137310.1016/B978-0-12-822688-9.00014-12-s2.0-85134545396Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengOptimum-Path Forest: Theory, Algorithms, and Applicationsinfo:eu-repo/semantics/openAccess2024-04-23T16:11:11Zoai:repositorio.unesp.br:11449/241373Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:45:12.880186Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest |
title |
Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest |
spellingShingle |
Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest Jodas, Danilo Samuel [UNESP] Atherosclerotic lesions Carotid artery Computer-aided diagnosis Medical images Optimum-path forest |
title_short |
Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest |
title_full |
Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest |
title_fullStr |
Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest |
title_full_unstemmed |
Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest |
title_sort |
Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest |
author |
Jodas, Danilo Samuel [UNESP] |
author_facet |
Jodas, Danilo Samuel [UNESP] Roder, Mateus [UNESP] Pires, Rafael [UNESP] Silva Santana, Marcos Cleison [UNESP] de Souza, Luis A. Passos, Leandro Aparecido [UNESP] |
author_role |
author |
author2 |
Roder, Mateus [UNESP] Pires, Rafael [UNESP] Silva Santana, Marcos Cleison [UNESP] de Souza, Luis A. Passos, Leandro Aparecido [UNESP] |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) São Carlos Federal University |
dc.contributor.author.fl_str_mv |
Jodas, Danilo Samuel [UNESP] Roder, Mateus [UNESP] Pires, Rafael [UNESP] Silva Santana, Marcos Cleison [UNESP] de Souza, Luis A. Passos, Leandro Aparecido [UNESP] |
dc.subject.por.fl_str_mv |
Atherosclerotic lesions Carotid artery Computer-aided diagnosis Medical images Optimum-path forest |
topic |
Atherosclerotic lesions Carotid artery Computer-aided diagnosis Medical images Optimum-path forest |
description |
Analysis of the atherosclerotic lesions deposited in the carotid artery is so far an essential task for estimating possible cardiovascular disorders in patients. The immediate assessment of such lesion, as well as its morphology and composition, turns out necessary to avoid its progression beforehand, thus preventing more severe conditions such as heart attacks and strokes caused by calcified elements observed in advanced stages. Heretofore, a number of works addressed medical diagnosis problems through computational approaches, developing Computer-Aided Diagnosis (CAD) tools to detect, among several applications, atherosclerotic plaques formed in carotid arteries. In this context, a graph-based machine learning framework called Optimum-Path Forest (OPF) was successfully employed to tackle several CAD-based problems, even though no one still explores the model to classify the task mentioned above. Therefore this paper proposes the classification of regions in atherosclerotic lesions as calcified or noncalcified debris through OPF-based approaches. In the process, handcrafted features are extracted from pixels of computed tomography angiography images of the carotid artery. Also, each pixel is labeled by an expert as a calcified or noncalcified element. Thereafter, the OPF classifier, as well as four variants, namely Fuzzy OPF, OPF. knn, Probabilistic OPF, and the OPF for anomaly detection, are compared for the task of predicting whether the pixel of the carotid artery stands for the calcium of the atherosclerotic lesion or not. © 2022 Copyright |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-24 2023-03-01T20:59:04Z 2023-03-01T20:59:04Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/bookPart |
format |
bookPart |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/B978-0-12-822688-9.00014-1 Optimum-Path Forest: Theory, Algorithms, and Applications, p. 137-154. http://hdl.handle.net/11449/241373 10.1016/B978-0-12-822688-9.00014-1 2-s2.0-85134545396 |
url |
http://dx.doi.org/10.1016/B978-0-12-822688-9.00014-1 http://hdl.handle.net/11449/241373 |
identifier_str_mv |
Optimum-Path Forest: Theory, Algorithms, and Applications, p. 137-154. 10.1016/B978-0-12-822688-9.00014-1 2-s2.0-85134545396 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Optimum-Path Forest: Theory, Algorithms, and Applications |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
137-154 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129549273137152 |