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Region based Coding of 3D Magnetic Resonance Images for Telemedicine Applications

by M.V.Subramanyam, R.Sumalatha
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 5 - Number 12
Year of Publication: 2010
Authors: M.V.Subramanyam, R.Sumalatha
10.5120/968-1067

M.V.Subramanyam, R.Sumalatha . Region based Coding of 3D Magnetic Resonance Images for Telemedicine Applications. International Journal of Computer Applications. 5, 12 ( August 2010), 1-3. DOI=10.5120/968-1067

@article{ 10.5120/968-1067,
author = { M.V.Subramanyam, R.Sumalatha },
title = { Region based Coding of 3D Magnetic Resonance Images for Telemedicine Applications },
journal = { International Journal of Computer Applications },
issue_date = { August 2010 },
volume = { 5 },
number = { 12 },
month = { August },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-3 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume5/number12/968-1067/ },
doi = { 10.5120/968-1067 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:54:08.374769+05:30
%A M.V.Subramanyam
%A R.Sumalatha
%T Region based Coding of 3D Magnetic Resonance Images for Telemedicine Applications
%J International Journal of Computer Applications
%@ 0975-8887
%V 5
%N 12
%P 1-3
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Region Based Coding (RBC) technique is significant for medical image compression and transmission. Lossless compression schemes with secure transmission play a key role in telemedicine applications that help in accurate diagnosis and research. In this paper we propose a lossless compression approach based on 3D integer wavelet transform, 3D SPIHT algorithm of MR images. The use of lifting scheme allows to generate truly lossless integer to integer wavelet transforms. The main objective of this work is rejects the noisy background and reconstructs the image portion losslessly. In this work different integer wavelet transforms will be used to compress the 3D MR images. The performance of the system has been evaluated based on bits-per-pixel and peak signal-to-noise ratio.

References
  1. Ahmed Abu-Hajar and Ravi Shankar, “Region of Interest Coding using Partial-SPIHT”, IEEE 2004.
  2. Calderbank AR, Daubechies I, Sweldens W, and Yeo BL: Wavelet transforms that map integers to integers. Appl Comput Harmon Anal 1998; 5: 332- 369.
  3. C.S.Gargour and V.Ramachandran, A Scheme for Teaching Wavelets at the Introductory Level, ASEE / IEEE Frontiers in Education Conference, 1997.
  4. I.Daubechies and W. Sweldens, Factoring Wavelet Transforms into Lifting Steps, Journal of Fourier analysis and Applications, Vol. 4, No. 3, pp. 245-267, 1998.
  5. Wavelets: Seeing the Forest and the Trees, Beyond Discovery: The Path from Research to Human Benefit, December 2001.
  6. W. Sweldens, Wavelets and the lifting scheme: A 5 minute Tour, Zeitschrift für Angewandte Mathematik und Mechanik, Vol. 76 (Suppl. 2), pp. 41-44, 1996.
  7. Zandi A, Allen JD, Schwartz EL, and Boliek M: CREW: Compression with reversible embedded wavelets. in Proc of Data Compression Conference 1995; 212-221.
Index Terms

Computer Science
Information Sciences

Keywords

3D SPIHT algorithm Integer Wavelet Transform Lossless compression Medical Image Compression Region Based Coding