The Refinement of Microcalcification Cluster Assessment by Joint Analysis of MLO and CC Views

  • Márta Altrichter
  • Gábor Horváth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4046)


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.


Joint Analysis Digital Mammography Pectoral Muscle Suspicious Region Microcalcification Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Márta Altrichter
    • 1
  • Gábor Horváth
    • 1
  1. 1.Department of Measurement and Information SystemsBudapest University of Technology and EconomicsBudapestHungary

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