Medical Image Compression Based on Region of Interest

Authors

  • Ahmed Madian Nano electronics Integrated System Center (NISC), Nile University, Cairo, Egypt
  • Dalia Shaaban Radiation Engineering Department, National Centre for Radiation Research and Technology (NCRRT), Egyptian Atomic Energy Authority, Cairo, Egypt
  • Hesham Elmahdy Department of Information Technology, Cairo University, Cairo, Egypt
  • Mohamed Saad Radiation Engineering Department, National Centre for Radiation Research and Technology (NCRRT), Egyptian Atomic Energy Authority, Cairo, Egypt
Abstract:

Medical images show a great interest since it is needed in various medical applications. In order to decrease the size of medical images which are needed to be transmitted in a faster way; Region of Interest (ROI) and hybrid lossless compression techniques are applied on medical images to be compressed without losing important data. In this paper, a proposed model will be presented and assessed based on size of the image, the Peak Signal to Noise Ratio (PSNR),and the time that is required to compress and reconstruct the original image.The major objective of the proposed model is to minimize the size of image and the transmission time. Moreover, improving the PSNR is a critical challenge.The results of the proposed model illustrate that applying hybrid losslesstechniques on the ROI of medical images reduces size by 39% and gives better results in terms of the compression ratio and PSNR.

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Journal title

volume 11  issue Special Issue

pages  29- 34

publication date 2019-07-01

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