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dc.contributor.authorGori, Ien
dc.contributor.authorBellotti, Ren
dc.contributor.authorCerello, Pen
dc.contributor.authorCheran, SCen
dc.contributor.authorNunzio, GDen
dc.contributor.authorFantacci, MEen
dc.contributor.authorKasae, Pen
dc.contributor.authorMasala, GLen
dc.contributor.authorMartinez, APen
dc.contributor.authorRetico, Aen
dc.date.accessioned2016-11-11T10:16:48Z
dc.date.available2016-11-11T10:16:48Z
dc.identifier.urihttp://hdl.handle.net/10026.1/6716
dc.description3 pages, 4 figures; Proceedings of the IEEE NNS and MIC Conference, Oct. 29 - Nov. 4, 2006, San Diego, Californiaen
dc.description.abstract

A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical Computed Tomography (CT) images with 1.25 mm slice thickness is presented. The basic modules of our lung-CAD system, a dot-enhancement filter for nodule candidate selection and a neural classifier for false-positive finding reduction, are described. The results obtained on the collected database of lung CT scans are discussed.

en
dc.language.isoenen
dc.subjectphysics.med-phen
dc.subjectphysics.med-phen
dc.titleLung Nodule Detection in Screening Computed Tomographyen
dc.typeJournal Article
plymouth.author-urlhttp://arxiv.org/abs/physics/0701161v1en
plymouth.publisher-urlhttp://dx.doi.org/10.1109/NSSMIC.2006.353752en
dc.identifier.doi10.1109/NSSMIC.2006.353752en
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics
dc.rights.embargoperiodNot knownen
rioxxterms.versionofrecord10.1109/NSSMIC.2006.353752en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.typeJournal Article/Reviewen


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