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Clusters of microcalcifications are often the earliest signs of breast cancer and their early detection is a primary consideration of screening programmes. We have previously presented a method to detect microcalcifications based on normalised images in standard mammogram form (SMF) using a foveal segmentation algorithm. In this paper, we discuss the selection and computation of parameters, which is a key issue in automatic detection methods. Deriving the parameters of our algorithm from image characteristics makes the method robust and essentially removes its dependence on parameters. We carry out a FROC analysis to study the behaviour of the algorithm on images prior to normalisation, as well as the contribution of the stages employed by our method. We report results from two different image databases. © Springer-Verlag Berlin Heidelberg 2004.


Conference paper

Publication Date





813 - 820