Advertisement

Expectation Maximization for Joint Deconvolution and Statistics Estimation

  • M. Alessandrini
  • A. Palladini
  • L. De Marchi
  • N. Speciale
Conference paper
Part of the Acoustical Imaging book series (ACIM, volume 30)

Abstract

Biomedical ultrasound image quality is limited due to the blurring of tissue reflectivity introduced by the transducer Point Spread Function (PSF). Deconvolution techniques can be used to obtain the pure tissue response, otherwise called reflectivity function. Typically deconvolution methods are developed in the only purpose of image visual quality improvement. In this work we present an Expectation Maximization (EM) framework for US images deconvolution in which local statistical description of the tissue reflectivity is restored as well, so that features extracted from the deconvolved frame can theoretically be used for classification purposes.

Keywords

Deconvolution Expectation maximization Generalized gaussian distribution 

References

  1. 1.
    Jensen, J.A.: A model for the propagation and scattering of ultrasound in tissue. J. Acoust. Soc. Am. 89(1), 182–190 (1991)Google Scholar
  2. 2.
    Kay, S.M.: Fundamentals of Statistical Signal Processing: Estimation Theory. Prentice- Hall Signal Processing Series (1993)Google Scholar
  3. 3.
    Taxt, T., Strand, J.: Two-dimensional noise-robust blind deconvolution of ultrasound images. IEEE Trans. Ultrason. Ferroelect. Freq. Contr. 48(4), 861–866 (2001)CrossRefGoogle Scholar
  4. 4.
    Michailovich, O.V., Adam, D.: Robust estimation of ultrasound pulses using outlier-resistant de-noising. IEEE Trans. Med. Imag. 22(3), 368–381 (2003)CrossRefGoogle Scholar
  5. 5.
    Katsaggelos, A.K.: Digital Image Restoration. Springer Series in Information Sciences, pp. 143–176 (1991)Google Scholar
  6. 6.
    Jirik, R., Taxt, T.: Two-dimensional blind bayesian deconvolution of medical ultrasound images. IEEE Trans. Ultrason. Ferroelect. Freq. Contr. 55(10), 2140–2153 (2008)CrossRefGoogle Scholar
  7. 7.
    Ng, J., Prager, R., Kingsbury, N., Treece, G., Gee, A.: Wavelet restoration of medical pulse-echo ultrasound images in an EM framework. IEEE Trans. Ultrason. Ferroelect. Freq. Contr. 54(3), 550–568 (2007)CrossRefGoogle Scholar
  8. 8.
    Michailovich, O.V., Adam, D.: A novel approach to 2-D blind deconvolution problem in medical ultrasound. IEEE Trans. Med. Imag. 24(1), 86–104 (2005)CrossRefGoogle Scholar
  9. 9.
    Bernard, O., Touil, B., D’Hooge, J., Friboulet, D.: Statistical modeling of the radio-frequency signal for partially- and fully-developed speckle based on a generalized gaussian model with application to echocardiography. IEEE Trans. Ultrason. Ferroelect. Freq. Contr. 54(10), 2189–2194 (2007)CrossRefGoogle Scholar
  10. 10.
    Donoho, D.: On minimum entropy deconvolution. In: Findley, D.F. (ed.) Applied Time Series Analysis II, pp. 565–608. Academic Press, New York (1981)Google Scholar
  11. 11.
    Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via EM algorithm. J. Roy. Stat. Soc. B 39(1), 1–38 (1997)MathSciNetGoogle Scholar
  12. 12.
    Blimes, J.A.: A Gentle Tutorial on the EM algorithm and its applications to parameter estimation for Gaussian Mixtures and Hidden Markov Models. http://crow.ee.washington.edu/people/bulyko/papers/em.pdf
  13. 13.
    Bioucas-Dias, J.M.: Bayesian wavelet-based image deconvolution: A GEM algorithm exploiting a class of heavy-tailed priors. IEEE Trans. Image Process. 15(4), 937–951 (2006)MathSciNetADSCrossRefGoogle Scholar
  14. 14.
    Figueiredo, M.A., Nowak, R.D.: An EM algorithm for wavelet-based image restoration. IEEE Trans. Image Process. 12(8), 906–916 (2003)MathSciNetADSCrossRefGoogle Scholar
  15. 15.
    Varanasi, M.K., Aazhang, B.: Parametric generalized Gaussian density estimation. J. Acoust. Soc. Am. 86(4), 1404–1415 (1989)ADSCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • M. Alessandrini
    • 1
  • A. Palladini
    • 1
  • L. De Marchi
    • 1
  • N. Speciale
    • 1
  1. 1.ARCES-DEISUniversity of BolognaBolognaItaly

Personalised recommendations