Use este identificador para citar ou linkar para este item: http://repositorio.ufc.br/handle/riufc/67208
Registro completo de metadados
Campo DCValorIdioma
dc.contributor.authorValente, Igor Rafael Silva-
dc.contributor.authorCortez, Paulo César-
dc.contributor.authorSoares, José Marques-
dc.contributor.authorCavalcanti Neto, Edson-
dc.contributor.authorAlbuquerque, Victor Hugo Costa de-
dc.contributor.authorTavares, João Manuel Ribeiro da Silva-
dc.date.accessioned2022-07-18T18:54:23Z-
dc.date.available2022-07-18T18:54:23Z-
dc.date.issued2016-
dc.identifier.citationSOARES, J. M. et al. Automatic 3D pulmonary nodule detection in CT images: A survey. Computer Methods and Programs in Biomedicine, vol. 124, p. 91-107, 2016pt_BR
dc.identifier.issn1872-7565-
dc.identifier.urihttp://www.repositorio.ufc.br/handle/riufc/67208-
dc.description.abstractThis work presents a systematic review of techniques for the 3D automatic detection of pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze the latest technology being used for the development of computational diagnostic tools to assist in the acquisition, storage and, mainly, processing and analysis of the biomedical data. Also, this work identifies the progress made, so far, evaluates the challenges to be overcome and provides an analysis of future prospects. As far as the authors know, this is the first time that a review is devoted exclusively to automated 3D techniques for the detection of pulmonary nodules from lung CT images, which makes this work of noteworthy value. The research covered the published works in the Web of Science, PubMed, Science Direct and IEEEXplore up to December 2014. Each work found that referred to automated 3D segmentation of the lungs was individually analyzed to identify its objective, methodology and results. Based on the analysis of the selected works, several studies were seen to be useful for the construction of medical diagnostic aid tools. However, there are certain aspects that still require attention such as increasing algorithm sensitivity, reducing the number of false positives, improving and optimizing the algorithm detection of different kinds of nodules with different sizes and shapes and, finally, the ability to integrate with the Electronic Medical Record Systems and Picture Archiving and Communication Systems. Based on this analysis, we can say that further research is needed to develop current techniques and that new algorithms are needed to overcome the identified drawbacks.pt_BR
dc.language.isoenpt_BR
dc.publisherComputer Methods and Programs in Biomedicinept_BR
dc.subject3D image segmentationpt_BR
dc.subjectComputer-aided detection systemspt_BR
dc.subjectLung cancerpt_BR
dc.subjectMedical image analysispt_BR
dc.subjectPulmonary nodulespt_BR
dc.titleAutomatic 3D pulmonary nodule detection in CT images: A surveypt_BR
dc.typeArtigo de Periódicopt_BR
Aparece nas coleções:DETE - Artigos publicados em revista científica

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
2016_art_jmsoares.pdf2,75 MBAdobe PDFVisualizar/Abrir


Os itens no repositório estão protegidos por copyright, com todos os direitos reservados, salvo quando é indicado o contrário.