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Abstract
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Article Information:
Comparison of Hybrid Codes for MRI Brain Image Compression
G. Soundarya and S. Bhavani
Corresponding Author: G. Soundarya
Submitted: March 18, 2012
Accepted: April 20, 2012
Published: December 15, 2012 |
Abstract:
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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.
Key words: Compression ratio , fractal, non-ROI, PSNR, ROI, segmentation,
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Cite this Reference:
G. Soundarya and S. Bhavani, . Comparison of Hybrid Codes for MRI Brain Image Compression. Research Journal of Applied Sciences, Engineering and Technology, (24): 5367-5371.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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