Compression Techniques for Medical Images Using SPIHT

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Medical imaging is important in trendy medical aid that gives diagnostic info for clinical management of patients and designing of treatment. Every year, terabytes of medical image data’s square measure used through advanced imaging modalities like Positron Emission Tomography (PET) Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and lots of additional new methodology of medical imaging. Advances in technology have created the chance for radiology systems to use complicated compression algorithms to scale back the file size of every image in an attempt to partly offset the rise in knowledge volume created by new or additional complicated modalities whereas protective the numerous diagnostic info. This paper outlines the various compression strategies like Discrete Cosine Transform (DCT), Fractal Compression and Set Partitioning In hierarchical Trees (SPIHT) applied to numerous medical pictures. Experimental results show that the projected SPIHT approach achieves the next Compression Ratio (CR), Bits Per Pixel (BPP) and Peak Signal to Noise Ratio (PSNR) with less Mean square Error (MSE) in comparison with DCT methodology.

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Edited by:

R. Edwin Raj, M. Marsaline Beno and M. Carolin Mabel

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87-94

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B. Perumal and M. P. Rajasekaran, "Compression Techniques for Medical Images Using SPIHT", Applied Mechanics and Materials, Vol. 626, pp. 87-94, 2014

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August 2014

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