Methodology for automatic detection of lung nodules in computerized tomography images

Detalhes bibliográficos
Autor(a) principal: Sousa, João Rodrigo Ferreira da Silva
Data de Publicação: 2010
Outros Autores: Silva, Aristófanes Corrêa, Paiva, Anselmo Cardoso de, Nunes, Rodolfo Acatauassú
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da UFMA
Texto Completo: http://gurupi.ufma.br:8080/jspui/1/304
Resumo: Também disponível em journal homepage: www.intl.elsevierhealth.com/journals/cmpb
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spelling Sousa, João Rodrigo Ferreira da SilvaSilva, Aristófanes CorrêaPaiva, Anselmo Cardoso deNunes, Rodolfo Acatauassú2010-10-14T13:33:10Z2010-10-14T13:33:10Z2010Sousa, João Rodrigo Ferreira da Silva ; Silva, Aristófanes Corrêa ; Silva, Anselmo Cardoso de; Nunes, Rodolfo Acatauassú. Methodology for automatic detection of lung nodules in computerized tomography images. Computer Methods and Programs in Biomedicine (Print), v. 98, p. 1-14, 2010.http://gurupi.ufma.br:8080/jspui/1/304Também disponível em journal homepage: www.intl.elsevierhealth.com/journals/cmpbLung cancer is a disease with significant prevalence in several countries around the world. Its difficult treatment and rapid progression make the mortality rates among people affected by this illness to be very high. Aiming to offer a computational alternative for helping in detection of nodules, serving as a second opinion to the specialists, this work proposes a totally automatic methodology based on successive detection refining stages. The automated lung nodules detection scheme consists of six stages: thorax extraction, lung extraction, lung reconstruction, structures extraction, tubular structures elimination, and false positive reduction. In the thorax extraction stage all the artifacts external to the patient’s body are discarded. Lung extraction stage is responsible for the identification of the lung parenchyma. The objective of the lung reconstruction stage is to prevent incorrect elimination of portions belonging to the parenchyma. Structures extraction stage comprises the selection of dense structures from inside the lung parenchyma. The next stage, tubular structures elimination eliminates a great part of the pulmonary trees. Finally, the false positive stage selects only structures with great probability to be nodule. Each of the several stages has very specific objectives in detection of particular cases of lung nodules, ensuring good matching rates even in difficult detection situations. We use 33 exams with diversified diagnosis and slices numbers for validating the methodology. We obtained a false positive per exam rate of 0.42 and false negative rate of 0.15. The total classification sensitivity obtained, measured out of the nodule candidates,was 84.84%. The specificity achieved was 96.15% and the total accuracy of the method was 95.21%.Submitted by Aparecida Cruz (cidazen@gmail.com) on 2010-10-14T13:33:10Z No. of bitstreams: 1 sdarticle.pdf: 970449 bytes, checksum: 457688002e6ae5851ceedc03472b1915 (MD5)Made available in DSpace on 2010-10-14T13:33:10Z (GMT). No. of bitstreams: 1 sdarticle.pdf: 970449 bytes, checksum: 457688002e6ae5851ceedc03472b1915 (MD5) Previous issue date: 2010ELSEVIERMedical imageComputer-aided detection (CAD)Lung nodulesImage processingComputer tomography (CT)Methodology for automatic detection of lung nodules in computerized tomography imagesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleporreponame:Repositório Institucional da UFMAinstname:Universidade Federal do Maranhão (UFMA)instacron:UFMAinfo:eu-repo/semantics/openAccessORIGINALsdarticle.pdfsdarticle.pdfapplication/pdf970449http://repositorio.ufma.br:8080/xmlui/bitstream/1/304/1/sdarticle.pdf457688002e6ae5851ceedc03472b1915MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81829http://repositorio.ufma.br:8080/xmlui/bitstream/1/304/2/license.txt89be553dc81c557318c8a1e0b2e1b451MD521/3042010-10-14 10:33:10.415oai:http://gurupi.ufma.br: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Repositório InstitucionalPUBhttp://repositorio.ufma.br:8080/oai/requestrepositorio@ufma.bropendoar:2010-10-14T13:33:10Repositório Institucional da UFMA - Universidade Federal do Maranhão (UFMA)false
dc.title.pt_BR.fl_str_mv Methodology for automatic detection of lung nodules in computerized tomography images
title Methodology for automatic detection of lung nodules in computerized tomography images
spellingShingle Methodology for automatic detection of lung nodules in computerized tomography images
Sousa, João Rodrigo Ferreira da Silva
Medical image
Computer-aided detection (CAD)
Lung nodules
Image processing
Computer tomography (CT)
title_short Methodology for automatic detection of lung nodules in computerized tomography images
title_full Methodology for automatic detection of lung nodules in computerized tomography images
title_fullStr Methodology for automatic detection of lung nodules in computerized tomography images
title_full_unstemmed Methodology for automatic detection of lung nodules in computerized tomography images
title_sort Methodology for automatic detection of lung nodules in computerized tomography images
author Sousa, João Rodrigo Ferreira da Silva
author_facet Sousa, João Rodrigo Ferreira da Silva
Silva, Aristófanes Corrêa
Paiva, Anselmo Cardoso de
Nunes, Rodolfo Acatauassú
author_role author
author2 Silva, Aristófanes Corrêa
Paiva, Anselmo Cardoso de
Nunes, Rodolfo Acatauassú
author2_role author
author
author
dc.contributor.author.fl_str_mv Sousa, João Rodrigo Ferreira da Silva
Silva, Aristófanes Corrêa
Paiva, Anselmo Cardoso de
Nunes, Rodolfo Acatauassú
dc.subject.por.fl_str_mv Medical image
Computer-aided detection (CAD)
Lung nodules
Image processing
Computer tomography (CT)
topic Medical image
Computer-aided detection (CAD)
Lung nodules
Image processing
Computer tomography (CT)
description Também disponível em journal homepage: www.intl.elsevierhealth.com/journals/cmpb
publishDate 2010
dc.date.accessioned.fl_str_mv 2010-10-14T13:33:10Z
dc.date.available.fl_str_mv 2010-10-14T13:33:10Z
dc.date.issued.fl_str_mv 2010
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.citation.fl_str_mv Sousa, João Rodrigo Ferreira da Silva ; Silva, Aristófanes Corrêa ; Silva, Anselmo Cardoso de; Nunes, Rodolfo Acatauassú. Methodology for automatic detection of lung nodules in computerized tomography images. Computer Methods and Programs in Biomedicine (Print), v. 98, p. 1-14, 2010.
dc.identifier.uri.fl_str_mv http://gurupi.ufma.br:8080/jspui/1/304
identifier_str_mv Sousa, João Rodrigo Ferreira da Silva ; Silva, Aristófanes Corrêa ; Silva, Anselmo Cardoso de; Nunes, Rodolfo Acatauassú. Methodology for automatic detection of lung nodules in computerized tomography images. Computer Methods and Programs in Biomedicine (Print), v. 98, p. 1-14, 2010.
url http://gurupi.ufma.br:8080/jspui/1/304
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv ELSEVIER
publisher.none.fl_str_mv ELSEVIER
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMA
instname:Universidade Federal do Maranhão (UFMA)
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instname_str Universidade Federal do Maranhão (UFMA)
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reponame_str Repositório Institucional da UFMA
collection Repositório Institucional da UFMA
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