Use of Quadrature Filters for Detection of Stellate Lesions in Mammograms

  • Hans Bornefalk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3540)

Abstract

We propose a method for finding stellate lesions in digitized mammograms based on the use of both local phase and local orientation information extracted from quadrature filter outputs. The local phase information allows efficient and fast separation between edges and lines and the local orientation estimates are used to find areas circumscribed by edges and with radiating lines. The method is incorporated in a computer-aided detection system and evaluation by FROC-curve analysis on a data set of 90 mammograms (45 pairs) yields a false positive rate of 0.3 per image at 90% sensitivity.

Keywords

Bright Line Digitize Mammogram Quadrature Filter False Positive Marking Spiculated Lesion 
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.

References

  1. 1.
    Tabar, L.: Control of breast cancer through screening mammography. Radiology 174, 655–656 (1990)Google Scholar
  2. 2.
    Tabar, L., Yen, M.-F., Vitak, B., Chen, H.-H.T., Smith, R.A., Duffy, S.W.: Mammography service screening and mortality in breast cancer patients: 20-year follow-up before and after introduction of screening. Lancet 361, 1405–1410 (2003)CrossRefGoogle Scholar
  3. 3.
    Freer, T.W., Ulissey, M.J.: Screening mammography with computer-aided detection: prospective study of 12,860 patients in a community breast center. Radiology 220, 781–786 (2001)CrossRefGoogle Scholar
  4. 4.
    Destounis, S.V., et al.: Can computer-aided detection with double reading of screening mammograms help decrease the false-negative rate? Initial experience. Radiology 232, 578–584 (2004)CrossRefGoogle Scholar
  5. 5.
    Karssemeijer, N., te Brake, G.M.: Detection of Stellate Distortions in Mammograms. IEEE Trans. Med. Im. 15(5), 611–619 (1996)CrossRefGoogle Scholar
  6. 6.
    te Brake, G.M., Karssemeijer, N.: Segmentation of suspicious densities in digital mammograms. Med. Phys. 28(2), 259–266 (2001)CrossRefGoogle Scholar
  7. 7.
    Kobatake, H., Yoshinaga, Y.: Detection of Spicules on Mammogram Based on Skeleton Analysis. IEEE Trans. Med. Im. 15(3), 235–245 (1996)CrossRefGoogle Scholar
  8. 8.
    Ng, S.L., Bischof, W.F.: Automated detection and classification of breast tumors. Comput. Biomed. Res. 25, 218–237 (1992)CrossRefGoogle Scholar
  9. 9.
    Kegelmeyer Jr., W.P.: Computer Detection of Stellate Lesions in Mammograms. In: Proc. SPIE, vol. 1660, pp. 446–454 (1992)Google Scholar
  10. 10.
    Bornefalk, H.: Use of phase and certainty information from quadrature filters in detection of stellate patterns in digitized mammograms. In: Proc. SPIE, vol. 5370, pp. 97–107 (2004)Google Scholar
  11. 11.
    Granlund, G.H., Knutsson, H.: Signal Processing for Computer Vision. Kluwer Academic Publishers, Dordrecht (1995)Google Scholar
  12. 12.
    Haglund, L.: Adaptive Multidimensional Filtering. PhD thesis, Linköping University, Sweden. Dissertation No. 284 (1992)Google Scholar
  13. 13.
    Cawley, G.C.: MATLAB Support Vector Machine Toolbox (v0.50β). University of East Anglia, School of Information Systems, Norwich (2000), http://theoval.sys.uea.ac.uk/~gcc/svm/toolbox
  14. 14.
    Heath, M., Bowyer, K.W., Kopans, D.: Current status of the Digital Database for Screening Mammography. In: Digital Mammography. Kluwer Academic Publishers, Dordrecht (1998)Google Scholar
  15. 15.
    Petrick, N., Sahiner, B., Chan, H., Helvie, M.A., Paquerault, S., Hadjiiski, L.M.: Breast cancer detection: Evaluation of a mass-detection algorithm for computer-aided diagnosis–Experience in 263 patients. Radiology 224, 217–224 (2002)CrossRefGoogle Scholar
  16. 16.
    Nishikawa, R.M., Giger, M.L., Doi, K., Metz, C.E., Yin, F., Vyborny, C.J., Schmidt, R.A.: Effect of case selection on the performance of computer-aided detection schemes Med. Phys. 21(2), 265–269 (1994)Google Scholar
  17. 17.
    Giger, M.L.: Current issues in CAD for mammography. In: Digital Mammography 1996, pp. 53–59. Elsevier Science, Philadelphia (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Hans Bornefalk
    • 1
  1. 1.Dep. of PhysicsKTHStockholmSweden

Personalised recommendations