Automated detection of lung nodules in low-dose computed tomography

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dc.creatorCascio, D.
dc.creatorCheran, S. C.
dc.creatorChincarini, A.
dc.creatorDe Nunzio, G.
dc.creatorDelogu, P.
dc.creatorFantacci, M. E.
dc.creatorGargano, G.
dc.creatorGori, I.
dc.creatorMasala, G. L.
dc.creatorMartinez, A. Preite
dc.creatorRetico, A.
dc.creatorSantoro, M.
dc.creatorSpinelli, C.
dc.creatorTarantino, T.
dc.date2007-07-18
dc.date.accessioned2026-07-07T08:19:01Z
dc.date.available2026-07-07T08:19:01Z
dc.descriptionA computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector computed-tomography (CT) images has been developed in the framework of the MAGIC-5 Italian project. One of the main goals of this project is to build a distributed database of lung CT scans in order to enable automated image analysis through a data and cpu GRID infrastructure. The basic modules of our lung-CAD system, consisting in a 3D dot-enhancement filter for nodule detection and a neural classifier for false-positive finding reduction, are described. The system was designed and tested for both internal and sub-pleural nodules. The database used in this study consists of 17 low-dose CT scans reconstructed with thin slice thickness (~300 slices/scan). The preliminary results are shown in terms of the FROC analysis reporting a good sensitivity (85% range) for both internal and sub-pleural nodules at an acceptable level of false positive findings (1-9 FP/scan); the sensitivity value remains very high (75% range) even at 1-6 FP/scan
dc.description4 pages, 2 figures: Proceedings of the Computer Assisted Radiology and Surgery, 21th International Congress and Exhibition, Berlin, Volume 2, Supplement 1, June 2007, pp 357-359
dc.identifierhttps://arxiv.org/abs/0707.2696
dc.identifierhttp://arxiv.org/abs/0707.2696
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/134631
dc.subjectMedical Physics
dc.titleAutomated detection of lung nodules in low-dose computed tomography
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