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Reseach Article

A Review of the Effective Techniques of Compression in Medical Image Processing

by Suma, V Sridhar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 97 - Number 6
Year of Publication: 2014
Authors: Suma, V Sridhar

Suma, V Sridhar . A Review of the Effective Techniques of Compression in Medical Image Processing. International Journal of Computer Applications. 97, 6 ( July 2014), 23-30. DOI=10.5120/17012-7291

@article{ 10.5120/17012-7291,
author = { Suma, V Sridhar },
title = { A Review of the Effective Techniques of Compression in Medical Image Processing },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 97 },
number = { 6 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 23-30 },
numpages = {9},
url = { },
doi = { 10.5120/17012-7291 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:23:25.171371+05:30
%A Suma
%A V Sridhar
%T A Review of the Effective Techniques of Compression in Medical Image Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 97
%N 6
%P 23-30
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

Medical image data (Ultrasonography, Computed Tomography, Magnetic Resonance Imaging etc. ) consumes maximum storage and utilize maximum bandwidth for transmission that often results in degradation of image quality. Due to these inherent issues in such type of images, compression is the only applicable technique explored in the due course of prior research work. Currently, there exists abundant research work on medical image compression considering lossy and lossless types, but the need of medical images to be compressed efficiently with optimal compression ratio is yet a question mark. This paper will perform an investigation of various techniques explored and discusses some of the efficient techniques explicitly among all the prior work. While reviewing the prior literatures, it was explored that although medical image compression is an emerging need, but it encounters higher dimensionality of challenges and complicatedness for catering the increasing demands of the medical science.

  1. Koller,L. 2011. The Evolution of Medical Imaging Technologies: Electric Meat and Physician's Shifting Gaze, EA-Journal. Vol. 2, pp. 3.
  2. Yanga,C-T, Chen, C-H, Yang, M-F . 2010. Implementation of a medical image file accessing system in co-allocation data grids, Future Generation Computer Systems. Elsevier. Vol. 26, pp. 1127-1140
  3. Feng, D. , Cai, W. , and Fulton, R . 2002. Dynamic image data compression in the spatial and temporal domains: clinical issues and assessment. IEEE Transaction on Information Technology in Biomedicine. Vol. 6, pp. 262-268, Issue. 4
  4. Portoni, L. , Combi, C. , Pinciroli, F. 2002. User-Oriented Views in Health Care Information Systems. IEEE Transactions on Biomedical Engineering. Vol. 49, No. 12
  5. Al-Shaykh, O. K. , and Mersereau, R. M. 1996. Lossy compression of noisy cardiac image sequences. IEEE Proc. of the Data Compression Conf. , pp. 43-52, Vol. 31
  6. De Bruijn F. J. , Slump C. H. . 1996. On the separation of quantum noise for cardiac X-ray image compression. Proc. of the 18th Annual Int. Conf. of the IEEE on Bridging Disciplines for Biomedicine. EMBS. Vol. 3, pp. 1226 - 1227
  7. Ramaswamy, A. , and Mikhael, W. B. 1996. A Mixed Transform Approach for Efficient Compression of Medical Images. IEEE Trans. on Medical Imaging. Vol. 15, No. 3
  8. http://www. newmediarepublic. com/dvideo/compression/adv05. html
  9. Said, A. , Pearlman, W. A. 1993. An Image Multiresolution Representation for Lossless and Lossy Compression. IEEE Transactions on Image Processing
  10. Liu, C. M. . Lossless Image Compression, Retreived from www. csie. nctu. edu. tw/~cmliu/Courses/Compression/chap7. pdf?
  11. Arsinte, R. , Miron, C. On the efficiency of the differential pulse code modulation in image coding and compression and an implementation on a digital signal processor based system. Retreived from citeseerx. ist. psu. edu/viewdoc/download?doi=10. 1. 1. 182. 4359&rep=rep1&type=pdf
  12. Acharya, T. , Tsai, P. S. 2005. JPEG2000 Standard for Image Compression: Concepts, Algorithms and VLSI Architectures. John Wiley & Sons, 21-Jan-2005 - Computers, pp. 296
  13. http://en. wikipedia. org/wiki/Lossless_JPEG
  14. Rane, S. D. , and Sapiro, G. 2001. Evaluation of JPEG-LS, the New Lossless and Controlled-Lossy Still Image Compression Standard for Compression of High-Resolution Elevation Data. IEEE Transactions on Geo-science and Remote Sensing, Vol. 39, No. 10
  15. Ghrare, S. E. , Ali, M. A. , Jumari, K. , and Ismail, M. 2009. An Efficient Low Complexity Lossless Coding Algorithm for Medical Images. American Journal of Applied Sciences. Vol. 6 (8), pp. 1502-1508
  16. http://www. digitalpreservation. gov/formats/fdd/fdd000139. shtml
  17. Chowdhury, M. M. H. , and Khatun, A. . 2012. Image Compression Using Discrete Wavelet Transform. IJCSI International Journal of Computer Science Issues. Vol. 9, Issue 4, No. 1
  18. http://www. jpeg. org/. demo/FAQJpeg2k/EBCOT-coding. htm
  19. Taubman,D. 2000. High Performance Scalable Image Compression with EBCOT. IEEE Transactions on Image Processing
  20. Sanchez, V. , Nasiopoulos, P. , Abugharbieh, R. 2008. Efficient Lossless Compression of 4-D Medical Images Based on the Advanced Video Coding Scheme. IEEE Transactions On Information Technology In Biomedicine, Vol. 12, No. 4
  21. Sanchez, V. , Nasiopoulos, P. , Abugharbieh, R. 2009. Symmetry-Based Scalable Lossless Compression of 3D Medical Image Data. IEEE Transactions On Medical Imaging. Vol. 28, No. 7
  22. Sanchez, V. , Nasiopoulos, P. , Abugharbieh, R. 2009. Novel Lossless fMRI Image Compression Based on Motion Compensation and Customized Entropy Coding. IEEE Transactions on Information Technology in Biomedicine. Vol. 13, No. 4
  23. Shaou-Gang Miaou, Fu-Sheng Ke, and Shu-Ching Chen. 2009. A Lossless Compression Method for Medical Image Sequences Using JPEG-LS and Interframe Coding. IEEE Transactions On Information Technology In Biomedicine. Vol. 13, No. 5
  24. Sanchez, V. , Nasiopoulos, P. , Abugharbieh, R. . 2010. 3-D Scalable Medical Image Compression With Optimized Volume of Interest Coding, IEEE Transactions on Medical Imaging. Vol. 29, No. 10
  25. Kim, K. J. , Kim, B. , Mantiuk, R. , Richter, T. , Lee, H. , Kang, H-S, Seo,J. , and Lee, K. H. 2010. A Comparison of Three Image Fidelity Metrics of Different Computational Principles for JPEG2000 Compressed Abdomen CT Images, IEEE transactions on medical imaging. Vol. 29, No. 8
  26. Dang, T. T. , Nguyen, S. K. , Vu, T. D. , Higuchi, S. 2009. Cross-point regions on multiple bit planes for lossless images compression. IET Image Processing
  27. Taquet, J. , and Labit, C. 2012. Hierarchical Oriented Predictions for Resolution Scalable Lossless and Near-Lossless Compression of CT and MRI Biomedical Images. IEEE Transactions on Image Processing. Vol. 21, No. 5
  28. Bairagi, V. K. Sapkal, A. M. 2011. Automated region-based hybrid compression for digital imaging and communications in medicine magnetic resonance imaging images for telemedicine applications. IET Science. Measurement and Technology
  29. Ansari, M. A. , Anand, R. S. , Recent trends in image compression and its application in telemedicine and Teleconsultation, national systems conference, NSC 2008, December 17-19, 2008
  30. Grgic, S. , Grgic, M. , Cihlar, B. Z. 2001. Performance Analysis of Image Compression Using Wavelets. IEEE Transactions on Industrial Electronics, Vol. 48, No. 3
  31. Kurnaz, M. N. , Dokur, Z. , and Olmez, T. 2002. Compression of MR andUltrasound Images by Using Wavelet Transform. Proc. of the 2nd Joint EMBS/BMES IEEE Conf. , Houston, pp. 1021-1022
  32. Wong, S. 1995. Radiologic Image Compression-A Review, IEEE Trans. on Medical Imaging. Vol. 83, No. 2
  33. LeeD. T. 2005. JPEG. 2000: Retrospective and New Developments, Proceedings of the IEEE. Vol. 93, No. 1
Index Terms

Computer Science
Information Sciences


Medical Image Processing Compression Techniques Lossy and Lossless Compression