الفهرس 
Improving Compression Techniques for Medical Images
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Abstract
Medical imaging show a great interest since it is needed in various medical applications. Medical image helps doctors to detect human’s diseases early. Nowadays many surgeries depends on the medical imaging. Medical imaging is a very critical issue as its data are sensitive. Medical images need large storage devices and high bandwidth for transmission. In order to decrease the size of medical images which is needed to be transmitted in a faster way; lossless compression methods are used. Lossless methods do not achieve high compression ratio as no losing of original data occurs. Region of Interest and lossless compression techniques are applied on medical images to be compressed and enhanced compression ratio. In this thesis, a proposed model will be presented and assessed based on different performance metrics. These metrics are size of the image, the compression ratio, the Peak Signal to Noise Ratio, the mean squared error, and the time that is required to compress and reconstruct the original image. The major objective of the proposed model is to improve PSNR with acceptable compression ratio. The proposed compression technique has been tested by different noises attacks