CADe tools for early detection of breast cancer

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dc.creatorBottigli, U.
dc.creatorCerello, P. G.
dc.creatorDelogu, P.
dc.creatorFantacci, M. E.
dc.creatorFauci, F.
dc.creatorForni, G.
dc.creatorGolosio, B.
dc.creatorLauria, A.
dc.creatorLopez, E.
dc.creatorMagro, R.
dc.creatorMasala, G. L.
dc.creatorOliva, P.
dc.creatorPalmiero, R.
dc.creatorRaso, G.
dc.creatorRetico, A.
dc.creatorStumbo, S.
dc.creatorTangaro, S.
dc.date2004-10-13
dc.date.accessioned2026-07-07T05:52:52Z
dc.date.available2026-07-07T05:52:52Z
dc.descriptionA breast neoplasia is often marked by the presence of microcalcifications and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. Our collaboration, among italian physicists and radiologists, has built a large distributed database of digitized mammographic images and has developed a Computer Aided Detection (CADe) system for the automatic analysis of mammographic images and installed it in some Italian hospitals by a GRID connection. Regarding microcalcifications, in our CADe digital mammogram is divided into wide windows which are processed by a convolution filter; after a self-organizing map analyzes each window and produces 8 principal components which are used as input of a neural network (FFNN) able to classify the windows matched to a threshold. Regarding massive lesions we select all important maximum intensity position and define the ROI radius. From each ROI found we extract the parameters which are used as input in a FFNN to distinguish between pathological and non-pathological ROI. We present here a test of our CADe system, used as a second reader and a comparison with another (commercial) CADe system.
dc.description4 pages, Proceedings of the 4th International Symposium on Nuclear and Related Techniques 2003, Vol. unico, pp. d10/1-d10/4 Havana, Cuba
dc.identifierhttps://arxiv.org/abs/physics/0410082
dc.identifierhttp://arxiv.org/abs/physics/0410082
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/86466
dc.subjectMedical Physics
dc.titleCADe tools for early detection of breast cancer
dc.typetext

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