INFORMATION CHANGE THE WORLD

International Journal of Information Engineering and Electronic Business(IJIEEB)

ISSN: 2074-9023 (Print), ISSN: 2074-9031 (Online)

Published By: MECS Press

IJIEEB Vol.8, No.3, May. 2016

Despeckling of Medical Ultrasound Images: A Technical Review

Full Text (PDF, 568KB), PP.11-19


Views:110   Downloads:8

Author(s)

Nidhi Gupta, A.P Shukla, Suneeta Agarwal

Index Terms

Despeckling;speckle noise;filtering mechanisms;wavelet thresholding

Abstract

Acquisition of digital image and preprocessing methods plays a vital role in clinical diagnosis. The ultrasound medical images are more popular than other imaging modalities, due to portable, adequate, harmless and cheaper nature of it. Because of intrinsic nature of speckle noise (signal based noise), ultrasound medical image leads to degradation of the resolution and contrast of the image. Reduction of this signal based noise is helpful for the purpose of visualization of the ultrasound images. The low quality of image is considered as a barrier for the better extraction of features, recognition, analysis and detection of edges. Because of which inappropriate diagnosis may be done by doctor. Thus, speckle noise reduction is essential and preprocessing step of ultrasound images. Analysts survey manifold reduction methods of speckle noise, yet there is no exact method that takes all the limitations into account. In this review paper, we compare filters that are Lee, Frost, Median, SRAD, PMAD, SRBF, Bilateral, Adaptive Bilateral and Multiresolution on medical ultrasound images. The results are compared with parameter PSNR along with the visual inspection. The conclusion is illustrated by filtered images and data tables.

Cite This Paper

Nidhi Gupta, A.P Shukla, Suneeta Agarwal,"Despeckling of Medical Ultrasound Images: A Technical Review", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.8, No.3, pp.11-19, 2016. DOI: 10.5815/ijieeb.2016.03.02

Reference

[1]Goodman, Joseph W. "Statistical properties of laser speckle patterns." Laser speckle and related phenomena. Springer Berlin Heidelberg, 1975. 9-75.

[2]F.Wagner, S.W. Smith, J.M.Sandrik, and H. Lopez, "Statistics of speckle in ultrasound B-scans," IEEE Trans. Sonics Ultrason., vol. 30, pp. 156–163, May 1983.

[3]Sehgal, "Quantitative relationship between tissue composition and scattering o of ultrasound," J. Acoust. Soc. Amer., vol. 94, pp. 1944–1952, Oct. 1993.

[4]T.Loupas, W. N. McDicken, and P. L. Allan, "An adaptive weighted median filtlaser for speckle suppression in medical ultrasound images," IEEE Trans. Circuits Syst., vol. 36, pp. 129–135, Jan. 1989. 

[5]M. Karaman, M. A. Kutay, and G. Bozdagi, "An adaptive speckle suppression filter for medical ultrasound imaging," IEEE Trans. Med. Imag., vol. 14, pp. 283–292, June 1995.

[6]C. Tomasi and R. Manduchi, "Bilateral filtering for gray And color images", in IEEE International Conference on Computer Vision, pp.839–846, 1998.

[7]Farzana, E., et al. "Adaptive bilateral filtering for despeckling of medical ultrasound images." TENCON 2010-2010 IEEE Region 10 Conference, IEEE, 2010.

[8]B. Zhang and J. P. Allebach "Adaptive bilateral filter for sharpness enhancement and noise removal", IEEE Trans. Image Process., vol. 17, no. 5, pp.664 -678 2008

[9]M. Zhang and B. K. Gunturk "Multiresolution bilateral filtering for image denoising", IEEE Trans. Image Process., vol. 17, no. 12, pp.2324 -2333 2008.

[10]A. K. Jain, Fundamental of Digital Image Processing. Englewood Cliffs, NJ: Prentice-Hall, 1989.

[11]X. Zong, A. F. Laine, and E. A. Geiser, "Speckle reduction and contrast enhancement of echocardiograms via multiscale nonlinear processing," IEEE Trans. Med. Imag., vol. 17, pp. 532–540, Aug. 1998.

[12]A. Achim, A. Bezerianos, and P. Tsakalides, "Novel Bayesian multiscale method for speckle removal in medical ultrasound images," IEEE Trans. Med. Imag., vol. 20, pp. 772–783, Aug. 2001.

[13]M. Tur, K. C. Chin, and J. W. Goodman, "When is speckle noise multiplicative?," Applied Optics, vol. 21, pp. 1157–1159, Apr. 1982.

[14]Jadwiga Rogowska and Mark E. Brezinski, "Evaluation of the adaptive speckle suppression filter for coronary optical coherence tomography imaging," IEEE Transactions on Medical Imageing, Vol. 19, No. 12, pp. 1261–1266, 2000.

[15]Yongjian Yu and Scott T. Acton, "Speckle reducing anisotropic diffusion," IEEE Transactions on Image Processing, Vol. 11, No. 11, pp. 1260–1270,2002.

[16]Joachim Weickert, "Anisotropic diffusion in image processing,"B.G. Teubner (Stuttgart), pp. 14–29, 1998.

[17]Simone Balocco, Carlo Gatta, Oriol Pajol, Josepa Mauri, and Petia Radeva, "SRBF: Speckle reducing bilateral filtering," Ultrasound in Medical & Biology, Vol. 36, No. 8, pp. 1353–1363, 2010.

[18]G. Wyszecki and W. S. Styles. Color Science: Concepts andMeth- . ods, Quantitative Data and Formulae. Wiley, New York, NY, 1982.

[19]A. Amer and E. Dubois, "Fast and reliable structure-oriented video noise estimation", in IEEE Trans. on Circuits and Systems for Video Technology, vol. 15, no. 1, pp. 113–118, 2005.

[20]M. Elad, "On the origin of the bilateral filter and the ways to improve it", in IEEE Trans. on Image Process., vol. 11, no.10, pp. 1141–1151, October, 2002.

[21]D. Barash, "Fundamental relationship between bilateral filtering, adaptive smoothing, and the nonlinear diffusion equation", in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 6, pp. 844–847, 2002.

[22]Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli,"Image quality assessment: from error visibility to structural similarity", in IEEE Trans. on Image Process., vol. 13, no. 4, pp. 600–612, April, 2004.

[23]R.Vanithamani and G.Umamaheswari "Wavelet based Despeckling of Medical Ultrasound Images with Bilateral filter", 2011, 389-393.

[24]G.Y.Chen,T.D.Bui and A.Krzyzak, "Image denoising using neighbouring wavelet coefficients" 2004,ICASSP, IEEE, pp. 917-920.

[25]S.Mallat, A theory for multiresolution signal decomposition: The wavelet representation, IEEE Trans. Patterns Anal. Machine Intell. 11 (1989) 674– 692.

[26]D.L. Donoho, I.M. Johnstone, "Ideal Spatial Adaptation via Wavelet Shrinkage", Biometrika, vol.81, pp.425~455, 1994.

[27]A. Buades, B. Coll, and J. Morel, "Neighborhood filters and PDE's," Numer. Math.,vol. 105, pp. 1–34, 2006.

[28]C. Kervrann and J. Boulanger, "Optimal spatial adaptation for patchbased image denoising," IEEE Trans. Image Process., vol. 15, no. 10, pp. 2866–2878, Oct. 2006.

[29]R. Sivakumar, M. K. Gayathri and D. Nedumaran, "Speckle filtering of Ultrasound B-scan images - A comparative study between spatial and diffusion filters," 2010 IEEE Conference on Open System (ICOS 2010), pp. 80-85, 2010.

[30]RamanMaini, Himanshu Aggarwal, "Performance evaluation of various speckle noise reduction filters on medical images," International Journal of Recent Trends in Engineering. Vol. 2, No. 4, pp. 22-25, 2009.

[31]Jadwiga Rogowska and Mark E. Brezinski, "Evaluation of the adaptive speckle suppression filter for coronary optical coherence tomography imaging," IEEE Transactions on Medical Imageing, Vol. 19, No. 12, pp. 1261-1266, 2000.