Active Contour Based Medical Image Segmentation and Compression Using Biorthogonal Wavelet and Embedded Zerotree

R  Loganathan   and Dr  Y  S  Kumaraswamy

doi:10.17485/ijst/2013/v6i4.21

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Active Contour Based Medical Image Segmentation and Compression Using Biorthogonal Wavelet and Embedded Zerotree

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2013/v6i4.21

Year: 2013, Volume: 6, Issue: 4, Pages: 1-6

Original Article

Active Contour Based Medical Image Segmentation and Compression Using Biorthogonal Wavelet and Embedded Zerotree

R. Loganathan^1* and Dr. Y. S. Kumaraswamy²

¹Research Scholar, Sathyabama University [email protected]
² Sr. Prof. & HOD, Dept. of MCA, DSCE [email protected]
*Author for Correspondence
R. Loganathan
Research Scholar, Sathyabama University
Email:[email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

This paper addresses medical image compression, as more and more medical images are digitized, economical and effective data compression technologies are needed to minimize the storage volume of medical database in hospitals. In this paper, the Region of Interest (ROI) – representing the diseased part - in a medical image is segmented using active contours. The ROI extracted are then compressed using lossless compression to maintain the integrity. A novel Biorthogonal wavelet and Embedded ZeroTree (EZW) is proposed for compression technique. Experimental results demonstrate that the proposed method significantly improves the Peak Signal to Noise Ratio (PSNR) for the medical image compression.
Keywords: Medical Images, Image Compression, Region of Interest, Active Contour, Biorthogonal Wavelets, Embedded ZeroTree (EZW).