Classification of calcified regions in atherosclerotic lesions of the carotid artery in computed tomography angiography images

dc.contributor.authorJodas, Danilo Samuel
dc.contributor.authorPereira, Aledir Silveira [UNESP]
dc.contributor.authorTavares, Joao Manuel R. S.
dc.contributor.institutionMinist Educ Brazil
dc.contributor.institutionUniv Porto
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-11T15:15:15Z
dc.date.available2020-12-11T15:15:15Z
dc.date.issued2020-04-01
dc.description.abstractThe identification of atherosclerotic plaque components, extraction and analysis of their morphology represent an important role towards the prediction of cardiovascular events. In this article, the classification of regions representing calcified components in computed tomography angiography (CTA) images of the carotid artery is tackled. The proposed classification model has two main steps: the classification per pixel and the classification per region. Features extracted from each pixel inside the carotid artery are submitted to four classifiers in order to determine the correct class, i.e. calcification or non-calcification. Then, geometrical and intensity features extracted from each candidate region resulting from the pixel classification step are submitted to the classification per region in order to determine the correct regions of calcified components. In order to evaluate the classification accuracy, the results of the proposed classification model were compared against ground truths of calcifications obtained from micro-computed tomography images of excised atherosclerotic plaques that were registered with in vivo CTA images. The average values of the Spearman correlation coefficient obtained by the linear discriminant classifier were higher than 0.80 for the relative volume of the calcified components. Moreover, the average values of the absolute error between the relative volumes of the classified calcium regions and the ones calculated from the corresponding ground truths were lower than 3%. The new classification model seems to be adequate as an auxiliary diagnostic tool for identifying calcifications and allowing their morphology assessment.en
dc.description.affiliationMinist Educ Brazil, CAPES Fdn, BR-70040020 Brasilia, DF, Brazil
dc.description.affiliationUniv Porto, Fac Engn, Inst Ciencia & Inovacao Engn Mecan & Engn Ind, Rua Dr Roberto Frias S-N, P-4200465 Porto, Portugal
dc.description.affiliationUniv Estadual Paulista, Rua Cristovao Colombo 2265, BR-15054000 Sao Jose Do Rio Preto, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Rua Cristovao Colombo 2265, BR-15054000 Sao Jose Do Rio Preto, Brazil
dc.format.extent2553-2573
dc.identifierhttp://dx.doi.org/10.1007/s00521-019-04183-z
dc.identifier.citationNeural Computing & Applications. London: Springer London Ltd, v. 32, n. 7, p. 2553-2573, 2020.
dc.identifier.doi10.1007/s00521-019-04183-z
dc.identifier.issn0941-0643
dc.identifier.urihttp://hdl.handle.net/11449/197726
dc.identifier.wosWOS:000522553100050
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofNeural Computing & Applications
dc.sourceWeb of Science
dc.subjectMedical imaging
dc.subjectPattern recognition
dc.subjectClassification
dc.subjectAtherosclerosis
dc.titleClassification of calcified regions in atherosclerotic lesions of the carotid artery in computed tomography angiography imagesen
dc.typeArtigo
dcterms.licensehttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dcterms.rightsHolderSpringer
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt
unesp.departmentCiências da Computação e Estatística - IBILCEpt

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