Number 10

A New Despeckling Method in Ultrasonography: Anisotropic Diffusion Filtering Followed by Total Variation Denoising

User Rating: 0 / 5

Star InactiveStar InactiveStar InactiveStar InactiveStar Inactive
 

Print

journal image
 Download
1499

Export

  • Kai Wang and Yingjie Liu and Liwen Zhang 2013. A New Despeckling Method in Ultrasonography: Anisotropic Diffusion Filtering Followed by Total Variation Denoising. International Journal of Applied Information Systems. 5, 10 (August 2013), 20-23. DOI=http://dx.doi.org/10.5120/ijais450978 
  • @article{10.5120/ijais2017451568,
author = {Kai Wang and Yingjie Liu and Liwen Zhang},
title = {A New Despeckling Method in Ultrasonography: Anisotropic Diffusion Filtering Followed by Total Variation Denoising},
journal = {International Journal of Applied Information Systems},
issue_date = {August 2013},
volume = {5},
number = {},
month = {August},
year = {2013},
issn = {},
pages = {20-23},
numpages = {},
url = {/archives/volume5/number10/515-0978},
doi = { 10.5120/ijais13-450978},
publisher = { xA9 2012 by IJAIS Journal},
address = {}
}

  • %1 450978
%A Kai Wang
%A Yingjie Liu
%A Liwen Zhang
%T A New Despeckling Method in Ultrasonography: Anisotropic Diffusion Filtering Followed by Total Variation Denoising
%J International Journal of Applied Information Systems
%@ 
%V 5
%N 
%P 20-23
%D 2013
%I  xA9 2012 by IJAIS Journal

Abstract

This paper proposes a novel hybrid method to reduce speckle noise in ultrasonography. This method applies the total variation denoising algorithm to the output image of a recently reported anisotropic diffusion filter. Performance of the proposed method is illustrated using simulated and clinical images. Experimental results indicate the proposed method outperforms the existing despeckling schemes in terms of both speckle reduction and edge preservation.

References

  1. Jain, A. K. 1989. Fundamental of digital processing. Upper Saddle River, NJ: Prentice-Hall.
  2. Perona, P. and Malik, J. 1990. Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. , 12 (7), 629-639.
  3. Yu, Y. and Acton, S. T. 2002. Speckle reducing anisotropic diffusion. IEEE Trans. Image Process. , 11 (11), 1260-1270.
  4. Yu, Y. and Acton, S. T. 2004. Edge detection in ultrasound imagery using the instantaneous coefficient of variation. IEEE Trans. Image Process. , 13 (12), 1640-1655.
  5. FernxE1ndez, S. A. and LxF3pez, C. A. 2006. On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering. IEEE Trans. Image Process. , 15 (9), 2694-2701.
  6. Li, C. , Wang, N. , Xiao, C. and Lu, X. 2012. A new speckle reducing anisotropic diffusion for ultrasonic speckle. Acta Automatica Sinica, 38 (3), 412-418.
  7. Rudin, L. , Osher, S. and Fatemi, E. 1992. Nonlinear total variation based noise removal algorithms. Physica D, 60, 259-268.
  8. Wang, Z. , Bovik, A. C. , Sheikh, H. R. and Simoncelli, E. P. 2004. Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. , 13 (4), 600-612.
  9. Xydeas, C. S. and Petrovic, V. 2000. Objective image fusion performance measure. Electron. Lett. , 36 (4), 308-309.

Keywords

Speckle, anisotropic diffusion, total variation denoising

Index Terms

Computer Science
Information Sciences