Observer Evaluations of Wavelet Methods for the Enhancement and Compression of Digitized Mammograms

  • Maria Kallergi
  • John J. Heine
  • Bradley J. Lucier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4046)


Two observer experiments were performed to evaluate the performance of wavelet enhancement and compression methodologies for digitized mammography. One experiment was based on the localization response operating characteristic (LROC) model. The other estimated detection and localization accuracy rates. The results of both studies showed that the two algorithms consistently improved radiologists’ performance although not always in a statistically significant way. An important outcome of this work was that lossy wavelet compression was as successful in improving the quality of digitized mammograms as the wavelet enhancement technique. The compression algorithm not only did not degrade the readers’ performance but it improved it consistently while achieving compression rates in the range of 14 to 2051:1. The proposed wavelet algorithms yielded superior results for digitized mammography relative to conventional processing methodologies. Wavelets are valuable and diverse tools that could make digitized screen/film mammography equivalent to its direct digital counterpart leading to a filmless mammography clinic with full inter- and intra-system integration and real-time telemammography.


Mammographic Density Digital Mammography Wavelet Method Observer Evaluation Observer Performance 
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  1. 1.
    Unser, M., Alroubi, A., Laine, A. (eds.): IEEE Trans. Med. Imaging, Special Issue on Wavelets in Medical Imaging (2003)Google Scholar
  2. 2.
    Kallergi, M., Clarke, L.P., Qian, W., et al.: Interpretation of calcifications in screen/film, digitized, and wavelet-enhanced, monitor displayed mammograms: an ROC study. Acad. Radiol. 3, 285–293 (1996)CrossRefGoogle Scholar
  3. 3.
    Qian, W., Clarke, L.P., Kallergi, M., Clark, R.A.: Tree structured nonlinear filters in digital mammography. IEEE Trans. Med. Imaging 13, 25–36 (1994)CrossRefGoogle Scholar
  4. 4.
    Heine, J.J., Kallergi, M., Chetelat, S.M., Clarke, L.P.: Multiresolution wavelet approach for sepa-rating the breast region from the background in high resolution digital mammography. In: Karssemeijer, N., Thijssen, M., Hendricks, J., van Erning, L. (eds.) Digital Mammography: proceedings of the 4th international workshop on digital mammography, pp. 295–298. Kluwer, The Netherlands (1998)Google Scholar
  5. 5.
    Heine, J.J., Velthuizen, R.P.: A statistical methodology for mammographic density detection. Med. Phys. 27, 2644–2651 (2000)CrossRefGoogle Scholar
  6. 6.
    Lucier, B.J., Kallergi, M., Qian, W., et al.: Wavelet compression and segmentation of mammographic images. J. Digit Imaging 7(1), 27–38 (1994)CrossRefGoogle Scholar
  7. 7.
    Yang, Z., Kallergi, M., DeVore, R., et al.: The effect of wavelet bases on the compression of digital mammograms. IEEE Eng. Med. Biol. 14(5), 570–577 (1995)CrossRefGoogle Scholar
  8. 8.
    Kallergi, M., Heine, J.J., Berman, C.G., Hersh, M.R., Romilly, A.P., Clark, R.A.: Improved interpretation of digitized mammography with wavelet processing: A localization response operating characteristic study. AJR 182, 697–703 (2004)Google Scholar
  9. 9.
    Kallergi, M., Lucier, B.J., Berman, C.G., Hersh, M.R., Kim, J.J., Szabunio, M.S., Clark, R.A.: High-Performance Wavelet Compression for Mammography: Localization Response Oper-ating Characteristic Evaluation. Radiology 238, 62–73 (2006)CrossRefGoogle Scholar
  10. 10.
    Heine, J.J., Deans, S.R., Cullers, D.K., Stauduhar, R., Clarke, L.P.: Multiresolution statistical analy-sis of high resolution digital mammograms. IEEE Trans. Med. Imaging 16, 503–515 (1997)CrossRefGoogle Scholar
  11. 11.
    Daubechies, I.: Ten Lectures on Wavelets. SIAM, Philadelphia (1992)MATHGoogle Scholar
  12. 12.
    Burgess, A.E.: Comparison of receiver operating characteristic and forced choice observer performance measurement methods. Med. Phys. 22(5), 643–655 (1995)CrossRefGoogle Scholar
  13. 13.
    Swensson, R.G.: Unified measurement of observer performance in detecting and localizing target objects on images. Med. Phys. 23, 1709–1725 (1996)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Maria Kallergi
    • 1
  • John J. Heine
    • 1
  • Bradley J. Lucier
    • 2
  1. 1.H. Lee Moffitt Cancer Center & Research InstituteCancer Control and PreventionTampaUSA
  2. 2.Department of MathematicsPurdue UniversityWest Lafayette

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