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    Abstract
2012 (Vol. 4, Issue: 24)
Article Information:

Comparison of Hybrid Codes for MRI Brain Image Compression

G. Soundarya and S. Bhavani
Corresponding Author:  G. Soundarya 

Key words:  Compression ratio , fractal, non-ROI, PSNR, ROI, segmentation,
Vol. 4 , (24): 5367-5371
Submitted Accepted Published
March 18, 2012 April 20, 2012 December 15, 2012
Abstract:

In general, medical images are compressed in a lossless manner in order to preserve details and to avoid wrong diagnosis. But this leads to a lower compression rate. Therefore, our aim is to improve the compression ratio by means of hybrid coding the MRI brain (tumor) images. Hence we consider Region of Interest (ROI) normally the abnormal region in the image and compress it without loss to achieve high compression ratio in par with maintaining high image quality and the Non-Region of Interest (Non-ROI) of the image is compressed in a lossy manner. This study discusses two simple hybrid coding techniques (Hybrid A and Hybrid B) on MRI human brain tumor image datasets. Also we evaluate their performance by comparing them with the standard lossless technique JPEG 2000 in terms of Compression Ratio (CR) and Peak to Signal Noise Ratio (PSNR). Both hybrid codes have resulted in computationally economical scheme producing higher compression ratio than existing JPEG2000 and also meets the legal requirement of medical image archiving. The results obtained prove that our proposed hybrid schemes outperform existing schemes.
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  Cite this Reference:
G. Soundarya and S. Bhavani, 2012. Comparison of Hybrid Codes for MRI Brain Image Compression.  Research Journal of Applied Sciences, Engineering and Technology, 4(24): 5367-5371.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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