An Enhanced N-Pattern Hybrid Technique for Medical Images in Telemedicine

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• 作者：Christy Sumitha Vincent^a ; ^{sumithathomasj@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Janet J.^b
• 关键词：Fuzzy C-Means ; Huffman Coding ; Mean Squared Error (MSE) ; Non-ROI ; Peak Signal-to-Noise Ratio (PSNR) ; ROI ; Telemedicine
• 刊名：Procedia Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：79
• 期：Complete
• 页码：305-313
• 全文大小：397 K

文摘

In the last couple of years, the communication technology has rapidly revolutionized the human society, whose benefits are not homogeneously felt by the nations. There are still network coverage problems in the under developed and developing nations. This scarcity of the bandwidth obviously hinders telemedicine technologies benefits being available to the major population of the society. So, the data compression will be of great support to overcome the bandwidth limitations. Hence, an effective hybrid compression technique has been introduced for the medical images in telemedicine. In this method, the considered medical image is being segmented into two parts namely, Region of Interest (ROI) and Non-Region of Interest (Non-ROI). The ROI are compressed using the lossless “Enhanced N-Pattern Huffman” compression algorithm. The Non-ROI is compressed using the lossy “JPEG” compression algorithm. This combined method improves the space saving that enhances effective transmission of the compressed data even in the scarce bandwidth network coverage areas and at the same time maintaining the quality of the relevant diagnostic information.