The Refinement of Microcalcification Cluster Assessment by Joint Analysis of MLO and CC Views
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.
KeywordsJoint Analysis Digital Mammography Pectoral Muscle Suspicious Region Microcalcification Cluster
Unable to display preview. Download preview PDF.
- 1.Yu, S., Guan, L.: A CAD System for the Automatic Detection of Clustered Microcalcifications in Digitized Mammogram Films. IEEE Trans. on Medical Imaging 19(2) (February 2000)Google Scholar
- 3.Ferrari, R.J., Rangayyan, R.M., Desautels, J.E.L., Borges, R.A., Frre, A.F.: Automatic Identification of the Pectoral Muscle in Mammograms. IEEE Trans. on Image Processing 23(2), 232–245 (2004)Google Scholar
- 5.Heath, M., Bowyer, K., Kopans, D., Moore, R., Chang, K., Munishkumaran, S., Kegelmeyer, P.: Current Status of the Digital Database for Screening Mammography. In: Karssemeier, N., Thijssen, M., Hendriks, J., van Erning, L. (eds.) Digital Mammography, Proc. of the 4th International Workshop on Digital Mammography, Nijmegen, pp. 457–460. Kluwer Acamdemic, The Netherlands (1998)Google Scholar