Abstract
Most of the CAD Systems for Mammograms are composed of algorithms analysing the four X-ray images individually. It is a general experience, that algorithms in search of microcalcification clusters can obtain high sensitivity only if specificity is low. To overcome efficiency problem this paper proposes a simple algorithm to combine information of the two views (MLO/CC) of the breast. The procedure is based upon the experiences of radiologists: masses and calcifications should emerge on both views, so if no matching is found, the given object is a false positive hit. A positioning system is evolved to find corresponding regions on the two images. Calcification clusters obtained in individual images are matched in “2.5-D” provided by the positioning system. The credibility value of the hit is reassessed by the matching. The proposed approach can significantly reduce the number of false positive hits in calcification.
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© 2006 Springer-Verlag Berlin Heidelberg
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Altrichter, M., Horváth, G. (2006). The Refinement of Microcalcification Cluster Assessment by Joint Analysis of MLO and CC Views. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds) Digital Mammography. IWDM 2006. Lecture Notes in Computer Science, vol 4046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11783237_69
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DOI: https://doi.org/10.1007/11783237_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35625-7
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