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Automatic classification of breast density
Oliver i Malagelada, Arnau; Freixenet i Bosch, Jordi; Zwiggelaar, Reyer
A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques
22-05-2010
Diagnòstic per la imatge
Imatges mèdiques -- Processament
Mama -- Radiografia
Radiografia mèdica -- Tècniques digitals
Breast -- Radiography
Diagnostic imaging
Imaging systems in medicine
Radiography, Medical -- Digital techniques
Tots els drets reservats
Artículo
IEEE
         

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