Lossless Medical Image Compression by Multi Oriented Prediction Technique

Authors

  • Renukadevi P. Research Scholar, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu. Author
  • Dr.M. Syed Mohomed Assistant Professor, Department of Computer Science, Sri Ram Nallamani Yadava College of Arts and Science, Tenkasi, Tamil Nadu. Author

DOI:

https://doi.org/10.61841/t1jfrv79

Keywords:

Multi Oriented Prediction Technique, Lossless Medical Image Compression

Abstract

Image compression plays a vital role in the medical field, in which the medical images can be transmitted from one place to another and need less space to store the data. The radiologist scans the patient’s interior part of the body by using some technology and instruments. Medical images are in the form of X-ray, CT, MRI, PET, etc. In hospitals and health centers, large amounts of medical image data are produced during the diagnosis of the patient. The proposed algorithms are tested over 325 cases of 3D medical images. The experimental results reveal that the proposed image compression and encryption system provides a high compression ratio, better bits per pixel, mean square error, less encryption and decryption time, better encryption quality, and good system performance as compared to existing approaches. The PSNR value for the 3D medical image is 56.4754, and the CT image PSNR value is 55.3924. 

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Published

31.07.2020

How to Cite

P. , R., & M. , S. M. (2020). Lossless Medical Image Compression by Multi Oriented Prediction Technique. International Journal of Psychosocial Rehabilitation, 24(5), 1277-1296. https://doi.org/10.61841/t1jfrv79