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Reseach Article

A Comparative Analysis of Different Wavelets for Enhancing Medical Ultrasound Images

by Dhrub Kumar, Maitreyee Dutta, Parveen Lehana
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 66 - Number 7
Year of Publication: 2013
Authors: Dhrub Kumar, Maitreyee Dutta, Parveen Lehana
10.5120/11094-5768

Dhrub Kumar, Maitreyee Dutta, Parveen Lehana . A Comparative Analysis of Different Wavelets for Enhancing Medical Ultrasound Images. International Journal of Computer Applications. 66, 7 ( March 2013), 7-11. DOI=10.5120/11094-5768

@article{ 10.5120/11094-5768,
author = { Dhrub Kumar, Maitreyee Dutta, Parveen Lehana },
title = { A Comparative Analysis of Different Wavelets for Enhancing Medical Ultrasound Images },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 66 },
number = { 7 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 7-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume66/number7/11094-5768/ },
doi = { 10.5120/11094-5768 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:21:42.555691+05:30
%A Dhrub Kumar
%A Maitreyee Dutta
%A Parveen Lehana
%T A Comparative Analysis of Different Wavelets for Enhancing Medical Ultrasound Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 66
%N 7
%P 7-11
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Ultrasound imaging is one of the popular imaging modalities used frequently by medical practitioners for diagnosis of diseases. But the problem with this technique is its low-resolution and the presence of speckle noise. This makes it difficult for the medical practitioners in studying and properly diagnosing the disease. In the past, researchers have enhanced the medical ultrasound images using various techniques like spatial-domain filtering, frequency domain filtering, histogram processing, morphological filtering and wavelets. Among these, wavelet based techniques have proved to be superior as compared to the rest of the techniques for enhancing medical ultrasound images. In this paper, a comparative analysis of different wavelet families has been carried out for enhancing medical ultrasound images. We have investigated the performance of Haar, Daubechies, Coiflet and Symlet wavelets of various orders using different decomposition levels and threshold selection methods to determine which one yields better enhancement results. The performance is evaluated using objective image quality parameters like Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR).

References
  1. Paul Suetens, "Fundamentals of Medical Imaging", 1st Edition, Cambridge University, U. K. , pp. 145-182, 2002.
  2. R. Sivakumar, D. Nedumaran, "Comparative study of Speckle Noise Reduction of Ultrasound B-scan Images in Matrix Laboratory Environment", International Journal of Computer Applications (0975 – 8887) vol. 10, no. 9, pp. 46-50, November 2010.
  3. Hasan Demirel and Gholamreza Anbarjafari, "Discrete Wavelet Transform-Based Satellite Image Resolution Enhancement", IEEE Transactions on Geoscience And Remote Sensing, vol. 49, no. 6, pp. 1997-2004, June 2011.
  4. D. L. Donoho,"Denoising by soft-thresholding", IEEE Transactions on Information Theory, vol. 41, pp 613-627, 1995.
  5. Rohit Sihag et al. , "Wavelet Thresholding for Image De-noising", International Conference on VLSI, Communication & Instrumentation (ICVCI), 2011.
  6. Rakesh Kumar and B. S. Saini, "Improved Image Denoising Technique Using Neighboring Wavelet Coefficients of Optimal Wavelet with Adaptive Thresholding", International Journal of Computer Theory and Engineering, vol. 4, no. 3, pp. 395-400, June 2012.
  7. P. S. Hiremath, Prema T. Akkasaligar, and Sharan Badiger," Speckle Reducing Contourlet Transform for Medical Ultrasound Images", World Academy of Science, Engineering and Technology 80, pp. 1217-1224, 2011.
  8. Yong Sun Kim and Jong Beom Ra, "Improvement of Ultrasound Image Based on Wavelet Transform: Speckle Reduction and Edge Enhancement", Medical Imaging 2005: Proc. of SPIE, vol. 5747, pp. 1085-1092 (SPIE, Bellingham, WA, 2005).
  9. Peter C. Tay, Christopher D. Garson, Scott T. Acton, and John A. Hossack, "Ultrasound Despeckling for Contrast Enhancement", IEEE Transactions on Image Processing, vol. 19, no. 7, pp. 1847-1860, July 2010.
  10. Banazier A. Abrahim and Yasser Kadah, "Speckle Noise Reduction Method Combining Total Variation and Wavelet Shrinkage for Clinical Ultrasound Imaging", 1ST Middle East Conference on Biomedical Engineering, pp. 80-83, 21-24 Feb. , 2011.
  11. D. Lee Fugal, "Conceptual Wavelets in Digital Signal Processing", Space & Signals Technical Publishing, San Diego, First edition, 2009.
  12. P. S. Hiremath, Prema T. Akkasaligar and Sharan Badiger, "Performance Comparison of Wavelet Transform and Contourlet Transform based methods for Despeckling Medical Ultrasound Images", International Journal of Computer Applications (0975 – 8887) vol. 26, no. 9, pp. 34-41, July 2011.
  13. Olawuyi, N. J, IROJU, O. G, IDOWU, C. S & OLALEKE, J. O, "Comparative Analysis of Wavelet-Based De-noising Algorithms on Cardiac Magnetic Resonance Images (MRIs)", African Journal of Computing & ICTs, vol. 4, no. 1, pp. 11-15, June 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Wavelet Discrete Wavelet transform Wavelet thresholding VisuShrink SUREShrink