@article{(Open Science Index):https://publications.waset.org/pdf/11639,
	  title     = {Quality Evaluation of Compressed MRI Medical Images for Telemedicine Applications},
	  author    = {Seddeq E. Ghrare and  Salahaddin M. Shreef},
	  country	= {},
	  institution	= {},
	  abstract     = {Medical image modalities such as computed
tomography (CT), magnetic resonance imaging (MRI), ultrasound
(US), X-ray are adapted to diagnose disease. These modalities
provide flexible means of reviewing anatomical cross-sections and
physiological state in different parts of the human body. The raw
medical images have a huge file size and need large storage
requirements. So it should be such a way to reduce the size of those
image files to be valid for telemedicine applications. Thus the image
compression is a key factor to reduce the bit rate for transmission or
storage while maintaining an acceptable reproduction quality, but it is
natural to rise the question of how much an image can be compressed
and still preserve sufficient information for a given clinical
application. Many techniques for achieving data compression have
been introduced. In this study, three different MRI modalities which
are Brain, Spine and Knee have been compressed and reconstructed
using wavelet transform. Subjective and objective evaluation has
been done to investigate the clinical information quality of the
compressed images. For the objective evaluation, the results show
that the PSNR which indicates the quality of the reconstructed image
is ranging from (21.95 dB to 30.80 dB, 27.25 dB to 35.75 dB, and
26.93 dB to 34.93 dB) for Brain, Spine, and Knee respectively. For
the subjective evaluation test, the results show that the compression
ratio of 40:1 was acceptable for brain image, whereas for spine and
knee images 50:1 was acceptable.},
	    journal   = {International Journal of Biomedical and Biological Engineering},
	  volume    = {6},
	  number    = {12},
	  year      = {2012},
	  pages     = {641 - 643},
	  ee        = {https://publications.waset.org/pdf/11639},
	  url   	= {https://publications.waset.org/vol/72},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 72, 2012},
	}