Abstract
Computer Assisted Diagnosis (CAD) is rapidly reaching worldwide acceptance in different fields of medicine. Particularly, CAD has found one of its main applications in breast cancer diagnosis where the detection of microcalcifications in women breasts is typically associated with the presence of cancer. In this paper, a method for automatic breast contour detection is presented as a pre-processing step for microcalcification detection. Then, a combination of scale-space algorithms are used to locate candidate regions of microcalcifications and a significant percentage of false positives are finally discriminated via thresholding. Detected regions using this method have been found to describe 91.6% of microcalcifications from the MIAS database with an average specificity of 97.30%.
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Pastrana Palma, A., Muñoz, J.F.R., Pérez, L.R.V., Aguilar, J.M.P., Álvarez, A.L. (2011). Computer Assisted Diagnosis of Microcalcifications in Mammograms: A Scale-Space Approach. In: Batyrshin, I., Sidorov, G. (eds) Advances in Artificial Intelligence. MICAI 2011. Lecture Notes in Computer Science(), vol 7094. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25324-9_44
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DOI: https://doi.org/10.1007/978-3-642-25324-9_44
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