Symbolic representation and classification of medical X-ray images
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://repositorio.inesctec.pt/handle/123456789/6723 http://dx.doi.org/10.1007/s11760-013-0486-6 |
Resumo: | In this paper, we propose a symbolic approach for classification of medical X-ray images. Graph cut segmentation is applied to segment the body part of medical X-ray images. A complete directed graph is constructed using the centroid points in the boundary image of the segmented body part image. The complete directed graph is in turn used to extract features of distance and orientation. Further, the boundaries of segmented images are represented by its skeleton end points. Shape features are then extracted from the represented skeleton end points. To assimilate feature variations, we propose to symbolically represent the extracted features of each class in the form of interval valued features. Based on the proposed symbolic representation, symbolic classifier is then used for classification of medical X-ray images. Experimental results reveal the efficiency of our proposed symbolic classification model. |
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Symbolic representation and classification of medical X-ray imagesIn this paper, we propose a symbolic approach for classification of medical X-ray images. Graph cut segmentation is applied to segment the body part of medical X-ray images. A complete directed graph is constructed using the centroid points in the boundary image of the segmented body part image. The complete directed graph is in turn used to extract features of distance and orientation. Further, the boundaries of segmented images are represented by its skeleton end points. Shape features are then extracted from the represented skeleton end points. To assimilate feature variations, we propose to symbolically represent the extracted features of each class in the form of interval valued features. Based on the proposed symbolic representation, symbolic classifier is then used for classification of medical X-ray images. Experimental results reveal the efficiency of our proposed symbolic classification model.2018-01-17T15:18:47Z2015-01-01T00:00:00Z2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/6723http://dx.doi.org/10.1007/s11760-013-0486-6engRajaei,AElham ShakibapourRangarajan,Linfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:38Zoai:repositorio.inesctec.pt:123456789/6723Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:25.977048Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Symbolic representation and classification of medical X-ray images |
title |
Symbolic representation and classification of medical X-ray images |
spellingShingle |
Symbolic representation and classification of medical X-ray images Rajaei,A |
title_short |
Symbolic representation and classification of medical X-ray images |
title_full |
Symbolic representation and classification of medical X-ray images |
title_fullStr |
Symbolic representation and classification of medical X-ray images |
title_full_unstemmed |
Symbolic representation and classification of medical X-ray images |
title_sort |
Symbolic representation and classification of medical X-ray images |
author |
Rajaei,A |
author_facet |
Rajaei,A Elham Shakibapour Rangarajan,L |
author_role |
author |
author2 |
Elham Shakibapour Rangarajan,L |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Rajaei,A Elham Shakibapour Rangarajan,L |
description |
In this paper, we propose a symbolic approach for classification of medical X-ray images. Graph cut segmentation is applied to segment the body part of medical X-ray images. A complete directed graph is constructed using the centroid points in the boundary image of the segmented body part image. The complete directed graph is in turn used to extract features of distance and orientation. Further, the boundaries of segmented images are represented by its skeleton end points. Shape features are then extracted from the represented skeleton end points. To assimilate feature variations, we propose to symbolically represent the extracted features of each class in the form of interval valued features. Based on the proposed symbolic representation, symbolic classifier is then used for classification of medical X-ray images. Experimental results reveal the efficiency of our proposed symbolic classification model. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01T00:00:00Z 2015 2018-01-17T15:18:47Z |
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 |
http://repositorio.inesctec.pt/handle/123456789/6723 http://dx.doi.org/10.1007/s11760-013-0486-6 |
url |
http://repositorio.inesctec.pt/handle/123456789/6723 http://dx.doi.org/10.1007/s11760-013-0486-6 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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