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• W1536783235 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." @default.
• W1536783235 created "2016-06-24" @default.
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• W1536783235 date "2013-04-20" @default.
• W1536783235 modified "2023-10-16" @default.
• W1536783235 title "Active Contour Based Medical Image Segmentation and Compression Using Biorthogonal Wavelet and Embedded Zerotree" @default.
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• W1536783235 doi "https://doi.org/10.17485/ijst/2013/v6i4.21" @default.
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