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Reseach Article

Comparative Study on Noise Reduction in Ultrasound Liver Images

by Mausumi Maitra, Somnath Dey, Manali Mukherjee
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 66 - Number 16
Year of Publication: 2013
Authors: Mausumi Maitra, Somnath Dey, Manali Mukherjee
10.5120/11167-6319

Mausumi Maitra, Somnath Dey, Manali Mukherjee . Comparative Study on Noise Reduction in Ultrasound Liver Images. International Journal of Computer Applications. 66, 16 ( March 2013), 13-16. DOI=10.5120/11167-6319

@article{ 10.5120/11167-6319,
author = { Mausumi Maitra, Somnath Dey, Manali Mukherjee },
title = { Comparative Study on Noise Reduction in Ultrasound Liver Images },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 66 },
number = { 16 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 13-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume66/number16/11167-6319/ },
doi = { 10.5120/11167-6319 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:22:33.842631+05:30
%A Mausumi Maitra
%A Somnath Dey
%A Manali Mukherjee
%T Comparative Study on Noise Reduction in Ultrasound Liver Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 66
%N 16
%P 13-16
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The gray scale digital image is an aggression of intensity values, represented in the form of two-dimensional array. But the digital images get corrupted by noise during acquisition and transmission. Noise is termed as any irrelevant data that obscures the authenticity of original data. Several noise removal algorithms are applied to ultrasound images in order to remove/reduce the noise level and improve the visual quality for better diagnoses. In the proposed method three algorithms named Median Filtering, Convolution and Wavelet Transform have been used on different ultrasound images and we have calculated the Relative Signal to Noise Ratio have been calculated for the measurement of image quality performance.

References
  1. Rafael C. Gonzalez, and Richard E. Woods, 2009 Digital Image Processing, Third Edition, Pearson Education.
  2. Somasundaram K and Shanmugavadivu P. 2009 Adaptive Iterative Order Statistics Filters, Journal of ICGST – GVIP, Vol. 09, pp. 23-32.
  3. R. Jain, R. Kasturi, and B. Schunck 1995 Machine Vision, McGraw-Hill.
  4. Behrooz Ghandeharian, Hadi Sadoghi Yazdi and Faranak Homayouni. 2009 Modified Adaptive center Weighted Median Filter for Suppressing Impulsive Noise in Images, International Journal of Research and Reviews in Applied Sciences, Vol. 01, No. 03.
  5. Gagnon,L. , A. Jouan. 1997 Speckle filtering of SAR images: A comparative study between complex-wavelet based and standard filters, in SPIE proc. , 3169,pp. 80-91.
  6. Halliwell, M. , P. N. T. Wells. 2001 Acoustical imaging chapter, In Ultrasonic Tissue haracterization, Johan M. Thijssen ed. , Springer U,pp. 189-197.
  7. Saad, A. S. 2008 Simultaneous speckle reduction and contrast enhancement for ultrasound images Wavelet versus Laplacian pyramid, Pattern Recognition and Image Analysis, 18, 63-70.
  8. http://www. ultrasound-images. com/liver. htm
  9. http://www. sono. nino. ru/english/hepar_en. html
  10. Mathworks Inc. Matlab R2007a, version 7. 4. 0. 287, January 29, 2007
  11. Hu Yueli, Ji Huijie ,2009 "Research on Image Median Filtering Algorithm and Its FPGA mplementation", IEEE Computer Society, pp. 226-230
  12. T. S. Huang, G. J. Yaw and C. Y. Tang. 1980 "A fast two dimensional median- filtering algorithm", IEEE Trans. Acoustic Speech and Signal Processing,ASSP-28, pp. 415-421.
  13. J. T. Astolla, and T. G. Campbell, 1989 "On computation of the running median", IEEE Trans. Acoustic Speech and Signal Processing, ASSP-37, pp. 572- 574.
  14. L. A. Christopher, 1988 W. T. Mayweather and S. S. Perlman, "VLSI median filter for impulse noise elimination in composite or component TV signals", IEEE Trans. On consumer Electronics, Val 34, no. 1, pp. 263-267,
Index Terms

Computer Science
Information Sciences

Keywords

Ultrasound Images SNR Median Convolution Wavelet