Skip to main content
SpringerLink
Log in

SPECKLE FORMATION, ANALYSIS AND PROCESSING APPLIED TO ULTRASOUND TISSUE CHARACTERIZATION

  • Conference paper
Physics for Medical Imaging Applications

Part of the book series: NATO Science Series ((NAII,volume 240))

  • 3171 Accesses

Abstract

This paper describes the image formation in medical ultrasound for the case of scattering media. The texture statistics are dominated by speckle formation which results from random interference of backscattered echoes. The effects of spatial, fixed and adaptive, filtering, as well as, of grey scale encoding on the detection of lesions are analytically described and illustrated with representative images.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Bamber, J.C., Daft, C., 1986. Adaptive filtering for reduction of speckle in ultrasonic pulseecho systems. Ultrasonics 24, 41–44.

    Article  Google Scholar 

  • Burckhardt, C.B., 1978. Speckle in ultrasound B-mode scans. IEEE Trans. Son. Ultrason. 25, 1–6.

    Google Scholar 

  • Cloostermans, M.J.T.M., Mol, H., Verhoef, J.A., Thijssen, J.M., 1986. In vitro estimation of acoustic parameters of the liver and correlations with histology. Ultrasound Med. Biol. 12, 39–51.

    Article  Google Scholar 

  • Cloostermans, M.J.T.M., Thijssen, J.M., 1983. A beam corrected estimation of the frequency dependent attenuation of biological tissues from backscattered ultrasound. Ultrason. Imag. 5, 136–147.

    Article  Google Scholar 

  • Dines, K.A., Kak, A.C., 1970. Ultrasonic attenuation tomography of soft tissues. Ultrason. Imag. 1, 16–33.

    Article  Google Scholar 

  • Dutt, V., Greenleaf, J.F., 1995. Speckle analysis using signal to noise ratios based on fractional order moments. Ultrason. Imag. 17, 251–268.

    Article  Google Scholar 

  • Dutt, V., Greenleaf, J.F., 1996. Statistics of log-compressed echo envelope. J. Acoust. Soc. Am. 99, 3817–3825.

    Article  ADS  Google Scholar 

  • Fellingham, L.L., Sommer, F.G., 1984. Ultrasonic characterization of tissue structure in the in vivo human liver and spleen. IEEE Trans. Son. Ultrason. 31, 418–428.

    Google Scholar 

  • Fink, M.A., Cardoso, J.F., 1984. Diffraction effects in pulseecho measurements. IEEE Trans. Son. Ultrason. 31, 313–329.

    Google Scholar 

  • Fink, M., Hottier, F., Cardoso, J.F., 1983. Ultrasonic signal processing for in vitro attenuation measurement: Short time Fourier analysis. Ultrason. Imag. 5, 117–135.

    Article  Google Scholar 

  • Foley, D., 1972. Considerations of sample and feature size. IEEE Trans. Inform. Theory 18, 618–626.

    Article  MATH  Google Scholar 

  • Gehlbach, S.M., Sommer, F.G., 1987. Speckle reduction processing. In: Proc. SPIE Int. Symp. Pattern Recogn. Acoust. Imag., Vol. 768.

    Google Scholar 

  • Giessen, R.J.B., Huynen, A.L., Aarnink, R.G., de la Rosette, J.J.M.C.H., Debruyne, F.M.J., Wijkstra, H., 1996. Construction and application of hierarchical decision tree for classification of ultrasonic prostate images. Med. Biol. Eng. Comp. 15, 105–109.

    Article  Google Scholar 

  • Goodman, J.W., 1975. Statistical properties of laser speckle. In: Dainty, J.C. (Ed.), Laser Speckle and Related Phenomena. Springer Verlag, Berlin, pp. 9–75.

    Chapter  Google Scholar 

  • Hao, X., Gao, S., Gao, X., 1999. A novel multiscale nonlinear thresholding method for ultrasonic speckle suppression. IEEE Trans. Med. Imag. 18, 787–794.

    Article  Google Scholar 

  • Haralick, R.M., Shanmugam, K., Dinastein, I., 1973. Textural features for image classification. IEEE Trans. Syst. Man Cyber. 3, 614–624.

    Google Scholar 

  • Huisman, H.J., Thijssen, J.M., 1996. Precision and accuracy of acoustospectrographic parameters. Ultrasound Med. Biol. 22, 855–871.

    Article  Google Scholar 

  • Huisman, H.J., Thijssen, J.M., 1998a. Adaptive feature extraction with application to ultrasonic image analysis. Ultrason. Imag. 20, 132–148.

    Google Scholar 

  • Huisman, H.J., Thijssen, J.M., 1998b. An in vivo model of liver parenchyma. IEEE Trans. Ultrason. Ferroel. Fre. Contr. 45, 739–750.

    Article  Google Scholar 

  • Insana, M.F., Wagner, R.F., Garra, B.S., Brown, D.G., Shawker, T.H., 1986. Analysis of ultrasound image texture via generalized Rician statistics. Opt. Eng. 25, 743–748.

    Google Scholar 

  • Jacobs, E.M.G.P., Thijssen, J.M., 1991. A simulation study of echographic imaging of structurally scattering media. Ultrason. Imag. 13, 316–333.

    Article  Google Scholar 

  • Jakeman, E., 1984. Speckle statistics with a small number of scatterers. Opt. Eng. 23, 453–461.

    ADS  Google Scholar 

  • Jakeman, E., Tough, R.J.A., 1987. Generalized k-distribution: A statistical model for weak scattering. J. Opt. Soc. Am. 4, 1764–1772.

    Article  ADS  Google Scholar 

  • Jongen, H.A.H., Thijssen, J.M., van der Aarssen, M., Verhoef, W.A., 1986. A general model for the absorption of ultrasound by biological tissues. J. Acoust. Soc. Am. 79, 535–540.

    Article  ADS  Google Scholar 

  • Kaplan, D., Ma, Q., 1994. On the statistical characterization of log-compressed Rayleigh signals. In: IEEE Ultrasonics Symposium.

    Google Scholar 

  • Klein Gebbink, M.S., Verhoeven, J.T.M., Thijssen, J.M., Schouten, T.E., 1993. Application of neural networks for the classification of diffuse liver disease by quantitative echography. Ultrason. Imag. 15, 205–217.

    Article  Google Scholar 

  • Kotropoulos, C., Pitas, I., 1992. Optimum nonlinear signal detection and estimation in the presence of ultrasonic speckle. Ultrason. Imag. 14, 249–275.

    Article  Google Scholar 

  • Kuc, R., Schwartz, M., von Micsky, L., 1976. Parametric estimation of the acoustic attenuation coefficient slope for soft tissue. In: IEEE Ultrason. Symp. Proc., no. 76 CH11200–SSU.

    Google Scholar 

  • Levinson, S.F., 1988. The ultrasonic investigation of dynamic muscle elasticity in vivo. J. Ultrasound Med. 7, 127 (abstract).

    Google Scholar 

  • Linzer, M., 1976. Ultrasonic tissue characterization I. NBS Special Publication, 453, Gaithersburg.

    Google Scholar 

  • Loupas, A., McDicken, W.N., Allan, P.L., 1989. An adaptive weighted median filter for speckle suppression in medical ultrasound images. IEEE Trans. Circ. Syst. 36, 129–135.

    Article  Google Scholar 

  • Magnin, P.A., Ramm, O.T., Thurstone, F.L., 1982. Frequency compounding for speckle contrast reduction in phased array images. Ultrason. Imag. 4, 267–281.

    Article  Google Scholar 

  • Mesdag, P.R., 1985. Estimation of medium parameters by acoustic echo measurements. Ph.D. Thesis, Technological University Delft, The Netherlands.

    Google Scholar 

  • Middleton, D., 1960. Introduction to Statistical Communication Theory. McGraw-Hill, New York.

    Google Scholar 

  • Momenan, R., Insana, M.F., Wagner, R.F., Garra, B.S., Brown, D.G., 1988. Application of cluster analysis and unsupervised learning to multivariate tissue characterization. J. Clin. Eng. 13, 455–461.

    Google Scholar 

  • Mountford, R.A., Wells, P.N.T., 1972. Ultrasonic liver scanning: The A-scan in the normal and cirrhosis. Phys. Med. Biol. 17, 261–269.

    Article  Google Scholar 

  • Nicholas, D., 1982. Evaluation of backscattering coefficients for excised tissues: Results, interpretation and associated measurements. Ultrasound Med. Biol. 8, 17–28.

    Article  Google Scholar 

  • Nicholas, D., Nassiri, D.K., Garbutt, P., Hill, C.R., 1986. Tissue characterization from ultrasound B-scan data. Ultrasound Med. Biol. 12, 135–143.

    Article  Google Scholar 

  • Oosterveld, B.J., Thijssen, J.M., Hartman, P.C., Romijn, R.L., Rosenbusch, G.J.E., 1991. Ultrasound attenuation in B-mode texture analysis of diffuse liver disease: Methods and preliminary results. Phys. Med. Biol. 36, 1031–1064.

    Article  Google Scholar 

  • Oosterveld, B.J., Thijssen, J.M., Hartman, P.C., Rosenbusch, G.J.E., 1993. Detection of diffuse liver disease by quantitative echography: Dependence on a priori choice of parameters. Ultrasound Med. Biol. 19, 21–25.

    Article  Google Scholar 

  • Oosterveld, B.J., Thijssen, J.M., Verhoef, W.A., 1985. Texture in B-mode echograms: 3-Dsimulations and experiments of the effects of diffraction and scatterer density. Ultrason. Imag. 7, 142–160.

    Article  Google Scholar 

  • Ophir, J., Cespedes, I., Ponnekanti, H., Yazdi, Y., Li, X., 1991. Elastography: A method for imaging the elasticity in biological tissues. Ultrason. Imag. 13, 111–134.

    Article  Google Scholar 

  • Papoulis, A., 1965. Probability, Random Variables and Stochastic Processes. McGraw Hill, New York.

    MATH  Google Scholar 

  • Rakotomamonjy, A., Deforge, P., March_e, P., 2000. Waveletbased speckle noise reduction in ultrasound B-scan images. Ultrason. Imag. 22, 73–94.

    Google Scholar 

  • Robinson, D.E., Ophir, J., Wilson, L.S., Chen, C.F., 1991. Pulse-echo ultra-sound speed measurement: Progress and prospects. Ultrasound Med. Biol. 17, 633–646.

    Article  Google Scholar 

  • Robinson, D.E., Wilson, L.S., Bianchi, T., 1984. Beam (diffraction) pattern correction for ultrasonic attenuation measurement. Ultrason. Imag. 6, 293–303.

    Article  Google Scholar 

  • Romijn, R.L., Thijssen, J.M., Delft, J.L., Wolff-Rouendaal, D., Best, J., Oosterhuis, J.A., 1989. In vivo ultrasound backscattering estimation for tumor diagnosis: An animal study. Ultrasound Med. Biol. 15, 471–479.

    Article  Google Scholar 

  • Romijn, R.L., Thijssen, J.M., Oosterveld, B.J., Verbeek, A.M., 1991. Ultrasonic differentiation of intracular melanoma: Parameters and estimation methods. Ultrason. Imag. 13, 27–55.

    Article  Google Scholar 

  • Schmitz, G., Ermert, H., 1999. Tissue characterization of the prostate using radiofrequency ultrasonic signals. IEEE Trans. Ultrason. Ferroel. Fre. Contr. 46, 126–138.

    Article  Google Scholar 

  • Sleefe, G.E., Lele, P.P., 1988. Tissue characterization based on scatterer number density estimation. IEEE Trans. Ultrason. Ferroel. Fre. Contr. 35, 749–757.

    Article  Google Scholar 

  • Smith, S.W., Wagner, R.F., Sandrik, J.M., Lopez, H., 1983. Low contrast detectability and contrast/detail analysis in medical ultrasound. IEEE Trans. Son. Ultrason. 30, 164–173.

    Google Scholar 

  • Swets, J.A., Pickett, R.M., 1982. Evaluation of Diagnostic Systems: Methods from Signal Detection Theory. Academic Press, New York.

    Google Scholar 

  • Thijssen, J.M., 1980. Ultrasonic Tissue Characterization: Clinical Achievements and Technological Potentials. Stafleu, Alphen aan den Rijn.

    Google Scholar 

  • Thijssen, J.M., 1992. Echographic image processing. In: Hawkins, P.W. (Ed.), Advances in Electronics and Electron Physics, Vol. 84. Academic Press, Boston, pp. 317–349.

    Google Scholar 

  • Thijssen, J.M., Cloostermans, M.J.T.M., Verhoef, W.A., 1981. Measurement of ultrasonic attenuation in tissues from scattering reflections: In vitro assessment of applicability. In: Thijssen, J.M., Verbeek, A.M. (Eds.), Ultrasonography in Ophthalmology 8. Dr.W. Junk Publishers, The Hague, pp. 431–439.

    Google Scholar 

  • Thijssen, J.M., Oosterveld, B.J., Hartman, P.C., Rosenbusch, G.J.E., 1993. Correlations between acoustic and texture parameters from rf- and B-mode liver echograms. Ultrasound Med. Biol. 19, 13–23.

    Article  Google Scholar 

  • Thijssen, J.M., Oosterveld, B.J., Wagner, R.F., 1988. Grey level transforms and lesion detectability in echographic images. Utrason. Imag. 10, 171–195.

    Article  Google Scholar 

  • Trahey, G.E., Allison, J.W., Smith, S.W., Ramm, O.T., 1986a. A quantitative approach to speckle reduction via frequency compounding. Ultrason. Imag. 8, 151–164.

    Article  Google Scholar 

  • Trahey, G.E., Smith, S.W., Ramm, O.T., 1986b. Speckle pattern correlation with lateral translation. IEEE Trans. Ultrason. Ferroel. Fre. Control 33, 257–264.

    Article  Google Scholar 

  • Valckx, F.M.J., Thijssen, J.M., 1997. Characterization of echographic image texture by cooccurrence matrix parameters. Ultrasound Med. Biol. 23, 559–571.

    Article  Google Scholar 

  • Valckx, F.M.J., Geemen, A.J., Thijssen, J.M., 1996. Online parametric ultrasound imaging. Ultrason. Imag. 18, 51.

    Google Scholar 

  • Valckx, F.M.J., Thijssen, J.M., Geemen, A.J., Rotteveel, J.J., 2000. Calibrated parametric ultrasound imaging. Ultrason. Imag. 22, 57–72.

    Google Scholar 

  • Varghese, T., Donehue, K.D., 1995. Estimating mean scatterer spacing with the frequencysmoothed spectral autocorrelation method. IEEE Trans. Ultrason. Ferroel. Fre. Contr. 42, 451–463.

    Article  Google Scholar 

  • Verhoeven, J.T.M., Thijssen, J.M., 1993. Improvement of lesion detectability by speckle reduction filtering: A quantitative study. Ultrason. Imag. 15, 181–204.

    Article  Google Scholar 

  • Verhoeven, J.T.M., Thijssen, J.M., Teeuwes, A.G.M., 1991. Improvement of lesion detection by echographic image processing: Signal-to-noise ratio imaging. Ultrason. Imag. 13, 238–251.

    Article  Google Scholar 

  • Verhoef, W.A., Cloostermans, M.J.T.M., Thijssen, J.M., 1985. Diffraction and dispersion effects on the estimation of ultrasound attenuation and velocity in biological tissues. IEEE Trans. Biomed. Eng. 32, 521–529.

    Article  Google Scholar 

  • Wagner, R.F., Insana, M.F., Brown, D.G., 1986. Unified approach to the detection and classification of speckle texture in diagnostic ultrasound. Opt. Eng. 25, 738–742.

    Google Scholar 

  • Wagner, R.F., Smith, S.W., Sandrik, J.M., Lopez, H., 1983. Statistics of speckle in ultrasound B-scans. IEEE Trans. Son. Ultrason. 30, 156–163.

    Google Scholar 

  • Wagner, R.F., Wear, K.A., Perez, J.E., McGill, J.B., Schechtman, K.B., Miller, J.G., 1995. Quantitative assessment of myocardial ultrasound tissue characterization through receiver operating characteristic analysis of Bayesian classifiers. J. Am. Coll. Cardiol. 25, 1706–1711.

    Article  Google Scholar 

  • Zong, X., Laine, A.F., Geisser, F.A., 1998. Speckle reduction and contrast enhancement of echocardiograms via multiscale non-linear processing. IEEE Trans. Med. Imag. 17, 532–540.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. 833 Clinical Physics Laboratory, University Children’s Centre, University Medical Centre Nijmegen, Nijmegen, 69101, 6500 HB, The Netherlands

    JOHAN M. THIJSSEN

Authors
  1. JOHAN M. THIJSSEN
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. European Scientific Institute, Site d'Archamps, Archamps, France

    Yves Lemoigne

  2. European Scientific Institute, Site d'Archamps, Archamps, France

    Alessandra Caner

  3. European Scientific Institute, Site d'Archamps, Archamps, France

    Ghita Rahal

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer

About this paper

Cite this paper

THIJSSEN, J.M. (2007). SPECKLE FORMATION, ANALYSIS AND PROCESSING APPLIED TO ULTRASOUND TISSUE CHARACTERIZATION. In: Lemoigne, Y., Caner, A., Rahal, G. (eds) Physics for Medical Imaging Applications. NATO Science Series, vol 240. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5653-6_13

Download citation

Publish with us

Policies and ethics

Search

Navigation