Advertisement

MORPHOLOGICAL METHOD OF MICROCALCIFICATIONS DETECTION IN MAMMOGRAMS

  • Marek Ustymowicz
  • Mariusz Nieniewski
Part of the Computational Imaging and Vision book series (CIVI, volume 32)

Abstract

Detection of microcalcifications (MCs) in mammograms for early breast cancer diagnosing is a widely investigated subject. A number of methods have been tried out so far, but obtained results are still not satisfactory. To avoid difficulties with comparisons of our results with others’, we present results obtained on mammograms from the Digital Database for Screening Mammography (DDSM), provided by the University of South Florida. In this study, a novel approach to MCs detection based on mathematical morphology is presented. A combination of methods is used for the detection of MCs. The evaluation of the proposed technique is done using a free-response operating characteristic (FROC). Our results demonstrate that the MCs can be effectively detected by the proposed approach.

Keywords

Gray Level Binary Image Digital Mammography Mathematical Morphology Digital Mammogram 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

REFERENCES

  1. 1.
    Lemaur, G., K. Drouiche, and J. DeConinck (2003). Highly Regular Wavelets for the Detection of Clustered Microcalcifications in Mammograms. IEEE Transactions on Medical Imaging, 22(3), 393–401.CrossRefGoogle Scholar
  2. 2.
    Cheng, H. D., J. Wang, and X. Shi (2004). Microcalcification Detection Using Fuzzy Logic and Scale Space Approaches. Pattern Recognition, 37(02), 363–375.CrossRefGoogle Scholar
  3. 3.
    Nieniewski, M. (1999). Morphological Method for Extraction of Microcalcifications in Mammograms for Breast Cancer Diagnosis (1999). Machine Graphics and Vision, 8(3), 427–448.Google Scholar
  4. 4.
    El-Naqa, I., Y. Yang, M. N. Wernick, N. P. Galatsanos, and R. M. Nishikawa (2002). A Support Vector Machine Approach for Detection of Microcalcifications. IEEE Transactions on Medical Imaging, 21(12), 1552–1563.CrossRefGoogle Scholar
  5. 5.
    Netsch, T. and H. O. Peitgen (1999). Scale-space Signatures for the Detection of Microcalcifications in Digital Mammograms. IEEE Transactions on Medical Imaging, 18(09), 774–786.CrossRefGoogle Scholar
  6. 6.
    Bazzani, A., A. Bevilacqua, D. Bollini, R. Brancaccio, R. Campanini, N. Lanconelli, A. Riccardi, and D. Romani (2001). An SVM Classifier to Separate False Signals From Microcalcifications in Digital Mammograms. Physics in Medicine and Biology, 46(6), 1651–1663.CrossRefGoogle Scholar
  7. 7.
    Gavrielides, M. A., J. Y. Lo, and C. E. Floyd, Jr. (2002) Parameter Optimization of a Computer-Aided Diagnosis Scheme for the Segmentation of Microcalcification Clusters in Mammograms. Medical Physics, 29(4), 475–483.CrossRefGoogle Scholar
  8. 8.
    Cheng, H. D., X. Cai, X. Chen, L. Hu, and X. Lou (2003). Computer-Aided Detection and Classification in Mammograms: a Survey. Pattern Recognition, 36(12), 2967–2991.CrossRefGoogle Scholar
  9. 9.
    Heath, M. K., D. Bowyer, R. Kopans, R. Moore, and P. Kegelmeyer, Jr. (2000). The Digital Data Base for Screening Mammography. 5th International Workshop on Digital Mammography, 212–218, Toronto, Canada, June 11–14, 2000.Google Scholar
  10. 10.
    Chakraborty, D. P. (2000). The FROC, AFROC and DROC Variants of the ROC Analysis. Ed. J. Beutel, H. L. Kundel, and R. L. Van Metter. Handbook of Medical Imaging. vol. 1: Physics and Psychophysics, SPIE Optical Engineering Press, 771–796, Bellingham, WA.Google Scholar
  11. 11.
    Ustymowicz, M. and M. Nieniewski (2004). Clustering Microcalcifications in Mammograms by Means of Morphology Based Strategy. 4th Benelux Signal Processing Symposium, 29–32, Hilvarenbeek, The Netherlands, April 15-16. 2004. http://www-ict.its.tudelft.nl/ieeesp/sps2004Google Scholar
  12. 12.
    Bruynooghe, M. and C. Messainguiral (2002). Detection of Very Subtle Microcalcification Clusters in High Resolution Full Field X-ray Mammograms. 6th International Workshop on Digital Mammography, 272–275, Bremen, Germany, June 22-25, 2002.Google Scholar
  13. 13.
    Lee, R., P. Alberdi, and P. Taylor (2000). A Comparative Study of Four Techniques for Calcification Detection. 5th International Workshop on Digital Mammography, 264–271, Toronto, Canada, June 11-14, 2000.Google Scholar

Copyright information

© Springer 2006

Authors and Affiliations

  • Marek Ustymowicz
    • 1
  • Mariusz Nieniewski
    • 2
  1. 1.Technical University of BialystokBialystokPOLAND
  2. 2.Institute of Fundamental Technological Research, PASWarsawPOLAND

Personalised recommendations