Multi-scale analysis of lung computed tomography images

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dc.creatorGori, I.
dc.creatorBagagli, F.
dc.creatorFantacci, M. E.
dc.creatorMartinez, A. Preite
dc.creatorRetico, A.
dc.creatorDe Mitri, I.
dc.creatorDonadio, S.
dc.creatorFulcheri, C.
dc.creatorGargano, G.
dc.creatorMagro, R.
dc.creatorSantoro, M.
dc.creatorStumbo, S.
dc.date2009-04-16
dc.date.accessioned2026-07-07T13:04:59Z
dc.date.available2026-07-07T13:04:59Z
dc.descriptionA computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
dc.description18 pages, 12 low-resolution figures
dc.identifierhttps://arxiv.org/abs/0904.2476
dc.identifierhttp://arxiv.org/abs/0904.2476
dc.identifier2007 JINST 2 P09007
dc.identifierdoi:10.1088/1748-0221/2/09/P09007
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/227360
dc.subjectMedical Physics
dc.titleMulti-scale analysis of lung computed tomography images
dc.typetext

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