An Automatic System to Discriminate Malignant from Benign Massive Lesions on Mammograms

dc.creatorRetico, A.
dc.creatorDelogu, P.
dc.creatorFantacci, M. E.
dc.creatorKasae, P.
dc.date2007-01-04
dc.date.accessioned2026-07-07T07:38:37Z
dc.date.available2026-07-07T07:38:37Z
dc.descriptionMammography is widely recognized as the most reliable technique for early detection of breast cancers. Automated or semi-automated computerized classification schemes can be very useful in assisting radiologists with a second opinion about the visual diagnosis of breast lesions, thus leading to a reduction in the number of unnecessary biopsies. We present a computer-aided diagnosis (CADi) system for the characterization of massive lesions in mammograms, whose aim is to distinguish malignant from benign masses. The CADi system we realized is based on a three-stage algorithm: a) a segmentation technique extracts the contours of the massive lesion from the image; b) sixteen features based on size and shape of the lesion are computed; c) a neural classifier merges the features into an estimated likelihood of malignancy. A dataset of 226 massive lesions (109 malignant and 117 benign) has been used in this study. The system performances have been evaluated terms of the receiver-operating characteristic (ROC) analysis, obtaining A_z = 0.80+-0.04 as the estimated area under the ROC curve.
dc.description6 pages, 3 figures; Proceedings of the ITBS 2005, 3rd International Conference on Imaging Technologies in Biomedical Sciences, 25-28 September 2005, Milos Island, Greece
dc.identifierhttps://arxiv.org/abs/physics/0701053
dc.identifierhttp://arxiv.org/abs/physics/0701053
dc.identifierNuclear Instruments and Methods in Physics Research A 569 (2006) 596-600
dc.identifierdoi:10.1016/j.nima.2006.08.093
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/121154
dc.subjectMedical Physics
dc.titleAn Automatic System to Discriminate Malignant from Benign Massive Lesions on Mammograms
dc.typetext

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