Lossless Compression on MRI Images Using SWT

Medical image compression is one of the growing research fields in biomedical applications. Most medical images need to be compressed using lossless compression as each pixel information is valuable. With the wide pervasiveness of medical imaging applications in health-care settings and the increase...

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Bibliographic Details
Published in:Journal of digital imaging 2014-10, Vol.27 (5), p.594-600
Main Authors: Anusuya, V., Raghavan, V. Srinivasa, Kavitha, G.
Format: Article
Language:English
Subjects:
Algorithms
Compressed
Computation
Data Compression - methods
Humans
Image compression
Imaging
Imaging, Three-Dimensional - methods
Lossless
Magnetic Resonance Imaging - methods
Medical
Medicine
Medicine & Public Health
Radiology
Random access
Streams
Telemedicine - methods
Wavelet Analysis
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Summary:Medical image compression is one of the growing research fields in biomedical applications. Most medical images need to be compressed using lossless compression as each pixel information is valuable. With the wide pervasiveness of medical imaging applications in health-care settings and the increased interest in telemedicine technologies, it has become essential to reduce both storage and transmission bandwidth requirements needed for archival and communication of related data, preferably by employing lossless compression methods. Furthermore, providing random access as well as resolution and quality scalability to the compressed data has become of great utility. Random access refers to the ability to decode any section of the compressed image without having to decode the entire data set. The system proposes to implement a lossless codec using an entropy coder. 3D medical images are decomposed into 2D slices and subjected to 2D-stationary wavelet transform (SWT). The decimated coefficients are compressed in parallel using embedded block coding with optimized truncation of the embedded bit stream. These bit streams are decoded and reconstructed using inverse SWT. Finally, the compression ratio (CR) is evaluated to prove the efficiency of the proposal. As an enhancement, the proposed system concentrates on minimizing the computation time by introducing parallel computing on the arithmetic coding stage as it deals with multiple subslices.
ISSN:0897-1889
1618-727X
DOI:10.1007/s10278-014-9697-9