DOI QR코드

DOI QR Code

Speckle Noise Reduction and Edge Enhancement in Ultrasound Images Based on Wavelet Transform

  • Kim, Yong-Sun (School of Electrical Engineering & Computer Science, Korea Advanced Institute of Science and Technology) ;
  • Ra, Jong-Beom (School of Electrical Engineering & Computer Science, Korea Advanced Institute of Science and Technology)
  • 발행 : 2008.04.30

초록

For B-mode ultrasound images, we propose an image enhancement algorithm based on a multi-resolution approach, which consists of edge enhancing and noise reducing procedures. Edge enhancement processing is applied sequentially to coarse-to-fine resolution images obtained from wavelet-transformed data. In each resolution, the structural features of each pixel are examined through eigen analysis. Then, if a pixel belongs to an edge region, we perform two-step filtering: that is, directional smoothing is conducted along the tangential direction of the edge to improve continuity and directional sharpening is conducted along the normal direction to enhance the contrast. In addition, speckle noise is alleviated by proper attenuation of the wavelet coefficients of the homogeneous regions at each band. This region-based speckle-reduction scheme is differentiated from other methods that are based on the magnitude statistics of the wavelet coefficients. The proposed algorithm enhances edges regardless of changes in the resolution of an image, and the algorithm efficiently reduces speckle noise without affecting the sharpness of the edge. Hence, compared with existing algorithms, the proposed algorithm considerably improves the subjective image quality without providing any noticeable artifacts.

키워드

참고문헌

  1. Macovski, Medical Imaging Systems, Prentice-Hall, 1983
  2. J. U. Quistgaard, 'Signal acquisition and processing in medical diagnostic ultrasound,' IEEE Signal Processing Magazine., vol. 14, pp. 67-74, 1997 https://doi.org/10.1109/79.560325
  3. P. N. T. Wells, 'Ultrasonic imaging of the human body,' Reports on Progress in Physics., vol. 62, pp. 671-722, 1995 https://doi.org/10.1088/0034-4885/62/5/201
  4. A. K. Jain, Fundamentals of Digital Image Processing. Englewood Cliffs, NJ: Prentice-Hall, 1989
  5. T. Loupas, W. N. Mcdicken, and P. L. Allan, 'An adaptive weighted median filter for speckle suppression in medical ultrasonic images,' IEEE Trans. Circuits Syst., vol. 36, pp. 129- 135, 1989 https://doi.org/10.1109/31.16577
  6. J. C. Bamber and C. Daft, 'Adaptive filtering for reduction of speckle in ultrasonic pulse-echo images,' Ultrasonics., pp. 41-44, 1986 https://doi.org/10.1016/0041-624X(86)90072-7
  7. J. Weickert, 'Multiscale texture enhancement,' in Computer Analysis of Images and Patterns; Lecture Notes in Computer Science, vol. 970, Springer, pp. 230-237, 1995
  8. K. Z. Abd-Elmoniem, A. M. Youssef, and Y. M. Kadah, 'Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion,' IEEE Trans. Biomedical Engineering., vol. 49, no. 9, pp. 997-1014, 2002 https://doi.org/10.1109/TBME.2002.1028423
  9. M. M. Goodsitt, P. L. Carson, S. Witt, D. L. Hykes, and J. M. Kofler, Jr., 'Real-time B-mode ultrasound quality control test procedures: Report of AAPM ultrasound task group no. 1,' Med. Phys., vol. 25, no. 8, pp. 1385-1406, 1998 https://doi.org/10.1118/1.598404
  10. N. M. Gibson, N. J. Dudley, and K. Griffith, 'A computerized quality control testing system for B-mode ultrasound,' Ultrasound in Med. & Biol., vol. 27, no. 12, pp. 1697-1711, 2001 https://doi.org/10.1016/S0301-5629(01)00479-3
  11. R. M. Rao and A. S. Bopardikar, Wavelet Transforms: Introduction to Theory and Applications., Addison Wesley Publications, 1998
  12. D. L. Donoho, 'De-noising by soft-thresholding,' IEEE Trans. Information theory., vol. 41, no. 3, pp. 613-627, 1995 https://doi.org/10.1109/18.382009
  13. X. Zong, A. F. Laine, and E. A. Geiser, "Speckle reduction and contrast enhancement of echocardiogram via multiscale Nonlinear Processing," IEEE Trans. Med. Imag., vol. 17, 1998
  14. Q. Zhou, L. Liu, D. Zhang, and Z. Bian, 'Denoise and contrast enhancement of ultrasound speckle image based on wavelet,' in Proc. International Conference on Signal Processing., 2002, pp. 1500-1503
  15. A. Achim, A. Bezerianos, and P. Tsakalides, 'Novel Bayesian multiscale method for speckle removal in medical ultrasound images,' IEEE Trans. Med. Imag., vol. 20, no. 8, pp. 772-783, 2001 https://doi.org/10.1109/42.938245
  16. X. Hao, S. Gao, and X. Gao, 'A novel multiscale nonlinear thresholding method for ultrasonic speckle suppressing,' IEEE Trans. Med. Imag., vol. 18, no. 9, pp. 787-794, 1999 https://doi.org/10.1109/42.802756
  17. A. Laine, J. Fan, and W. Yang, 'Wavelets for contrast enhancement of digital mammography,' IEEE Eng. Med. Biol., pp. 536-550, 1995
  18. P. Sakellaropoulos, L. Costaridou, and G. Panayiotakis, 'A wavelet-based spatially adaptive method for mammographic contrast enhancement,' Phys. Med. Biol., vol. 48, pp. 787-803, 2003 https://doi.org/10.1088/0031-9155/48/6/307
  19. Y. Xu, J. B. Weaver, D. M. Healy, and J. Lu, 'Wavelet transform domain filters: a spatially selective noise filtration technique,' IEEE Trans. Image Processing., vol. 3, no. 6, pp. 747-758, 1994 https://doi.org/10.1109/83.336245
  20. W H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical recipes in C - The art of scientific computing, Cambridge University press, pp. 463-469