Pulmonary nodule classification aided by clustering

dc.contributor.authorLee, S.L.A.
dc.contributor.authorKouzani, A.Z.
dc.contributor.authorNasierding, G.
dc.contributor.authorHu, E.J.
dc.contributor.conference2009 IEEE International Conference on Systems, Man and Cybernetics (SMC 2009) (11 Oct 2009 - 14 Oct 2009 : San Antonio, TX)
dc.date.issued2009
dc.description.abstractLung nodules can be detected through examining CT scans. An automated lung nodule classification system is presented in this paper. The system employs random forests as its base classifier. A unique architecture for classification-aided-by-clustering is presented. Four experiments are conducted to study the performance of the developed system. 5721 CT lung image slices from the LIDC database are employed in the experiments. According to the experimental results, the highest sensitivity of 97.92%, and specificity of 96.28% are achieved by the system. The results demonstrate that the system has improved the performances of its tested counterparts.
dc.description.statementofresponsibilityS.L.A. Lee, A.Z. Kouzani, and G. Nasierding, E.J. Hu
dc.identifier.citationConference proceedings / IEEE International Conference on Systems, Man, and Cybernetics. IEEE International Conference on Systems, Man, and Cybernetics, 2009, pp.906-911
dc.identifier.doi10.1109/ICSMC.2009.5346753
dc.identifier.isbn9781424427932
dc.identifier.issn1062-922X
dc.identifier.orcidHu, E.J. [0000-0002-7390-0961]
dc.identifier.urihttp://hdl.handle.net/2440/87431
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartofseriesIEEE International Conference on Systems Man and Cybernetics Conference Proceedings
dc.rights©2009 IEEE
dc.source.urihttps://doi.org/10.1109/icsmc.2009.5346753
dc.subjectclassification aided by clustering
dc.subjectnodule
dc.subjectdetection
dc.titlePulmonary nodule classification aided by clustering
dc.typeConference paper
pubs.publication-statusPublished

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