Speckle supression for medical ultrasound images based on modelling speckle with Rayleigh distribution in contourlet domain

Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR

Volumn 1, Issue , 2008, Pages 194-199

  Song, Xiao Yang ^a   Zhang, Su ^a   Song, Ke Ou ^b   Yang, Wei ^a   Chen, Ya Zhu ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b HARBIN ENGINEERING UNIVERSITY   (China)

Author keywords

Contourlet transform; Medical ultrasound image; Rayleigh distribution; Speckle suppression

Indexed keywords

ACOUSTIC WAVES; FEATURE EXTRACTION; FISCHER-TROPSCH SYNTHESIS; IMAGE ENHANCEMENT; PATTERN RECOGNITION; POLARIZATION; ULTRASONIC IMAGING; ULTRASONICS; WAVELET ANALYSIS; WAVELET TRANSFORMS;

CONTOURLET DOMAINS; CONTOURLET TRANSFORM; CONTOURLET TRANSFORMS; DENOISING TECHNIQUES; FINE FEATURES; MAXIMUM A POSTERIOR ESTIMATORS; MEDICAL ULTRASOUND IMAGE; MEDICAL ULTRASOUND IMAGES; MEDICAL ULTRASOUNDS; RAYLEIGH DISTRIBUTION; RAYLEIGH DISTRIBUTIONS; SPECKLE REDUCTIONS; SPECKLE SUPPRESSION; SPECKLE SUPPRESSIONS; SUPRESSION; ULTRASOUND IMAGES;

SPECKLE;

EID: 56849124163     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICWAPR.2008.4635775     Document Type: Conference Paper

References (25)

1. J. C. Bamber and C. Daft, "Adaptive filtering for reduction of speckle in ultrasonic pulse-echo images" Ultrasonics, pp. 41-44, 1986.
2. A. Ioannidis, D. Kazakos, and D. D. Watson, "Application of median filtering on nuclear medicine scintigram images," in Proc. 7th Int. Conf. Pattern Recognition, 1984, pp. 33-36.
3. A. K. Jain, Fundamental of Digital Image Processing. Englewood Cliffs, NJ: Prentice-Hall, 1989.
4. 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, Jan. 1989.
5. 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.
6. X. Hao, S. Gao, and X. Gao, "A novel multiscale nonlinear thresholding method for ultrasound speckle suppressing", IEEE Trans. Med. Imag., vol. 18, pp. 787-794, Sep. 1999.
7. 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.
8. M. N. Do and M. Vetterli, "The contourlet transform: an efficient directional multiresolution image representation", IEEE Transactions on Image Processing, Vol. 14, No. 12, pp. 2091-2106, Dec. 2005.
9. Z. F. Zhou and P. L. Shui, "Contourlet-based image denoising algorithm using directional windows", Electronics Letters, Vol. 43, Issue 2, pp. 92-93, 2007.
10. W. Ni, B. L.Guo, Y. Y.Yan, and L. Yang, "Speckle suppression for SAR images based on adaptive shrinkage in contourlet domain", Wcica 2006: Sixth World Congress on Intelligent Control and Automation, Vol. 1-12, pp. 10017-10021, June 2006.
11. H. H. Song, S.Y. Yu, C. Wang, L. Song, and H.K. Xiong, "A new deblocking algorithm based on adjusted contourlet transform", IEEE International Conference on Multimedia and Expo, pp. 449-452, Toronto, Ont., Canada, July 2006.
12. A.Bouzidi and N.Baaziz, "Contourlet domain feature extraction for image content authentication", IEEE Workshop on Multimedia Signal Processing, pp. 202-206, Victoria, BC, Canada, October 2006.
13. Q.G.Miao and B. S Wang, "The contourlet transform for image fusion", SPIE Conference on Multisensor, Multisource Informatin Fusion: Architectures, Algorithms, and Applications, Vol. 6242, Kissimmee, FL, USA, April 2006.
14. Y. A. Zheng, C. S. Zhu, J. S. Song, and X. H. Zhao, "Fusion of multi-band SAR images based on contourlet transform", IEEE International Conference on Information Acquisition, vol. 1-2, pp. 420-424, Weihai, China, August 2006.
15. P. Feng, Y. J. Pan, B. Wei, W. Jin, and D. L. Mi, "Enhancing retinal image by the Contourlet transform", Pattern Recognition Letters, Vol. 28, Issue 4, pp. 516-522, March 2007.
16. R. Zewail, M. Mandal, and N. Durdle, "Iris identification using contourlet transform", SPIE Proc.: Image Processing: Algorithms and Systems V, Vol. 6497, pp. 6497C 1-8, San Jose, CA, USA, 2007.
17. th IEEE-EMBS International Summer School and Symposium on Medical Devices and Biosensors, Cambridge, UK, pp. 107-110, August 2007.
18. R. F. Wagner, S.W.Smith, J.M.Sandrik, and H.Lopez, "Statistics of speckle in ultrasound B-scans", IEEE Trans. Sonics Ultrason. , Vol 30, No.3, pp. 156-163, 1983.
19. C. Burckhardt, "Speckle in ultrasound B-mode scans", IEEE Trans. Sonics Ultrason., Vol. 25, pp.1-6, 1978.
20. A. Papoulis, Probability random variables and stochastic processes, MHL, New York, USA, 1991.
21. A. Synyavskyy, S. Voloshynovskiy, and I. Prudyus, "Wavelet based MAP image denoising using provably better class of stochastic I.I.D. image models", Electron. Energetics Facta Univ., Vol. 14, No.3, 2001.
22. S. Gupta, R.C. Chauhan, and S.C. Saxena, "Locally adaptive wavelet domain Bayesian processor for denoising medical ultrasound images using Speckle modeling based on Rayleigh distribution", IEE Proc.-Vis. Image Signal Process., Vol. 152, No.1, Feb. 2005.
23. S. M. Phoong, C. W. Kim, P. P. Vaidyanathan, and R. Ansari, "A new class of two-channel biorthogonal filter banks and wavelet bases," IEEE Transactions on Signal Processing, vol. 43, no. 3, pp. 649-665, March 1995.
24. L. Gagnon and A. Jouan, "Speckle filtering of SAR images - A comparative study between complex-wavelet based and standard filters", in SPIE Proc., Vol. 3169, pp. 80-91, 1997.
25. F. Sattar, L. Floreby, G. Salomonsson, and B. Lovstrom, "Image enhancement based on a nonlinear multiscale method," IEEE Transactions on Image Processing, Vol. 6, No. 6, pp. 888-895, June 1997.