Medical Image Analysis and Achieving Compression using Hybrid Lossless and Lossy Compression Technique

Medical images like X-ray, CT or MRI produces visual representation of inner body structure. To recognize and name the exact character of a disease or a problem of human health condition, medical imaging is best method for them. For storage & transmission purpose there exist a need for compression of these images. Current compression schemes provide a very high compression rate with a considerable loss of quality. In medical imaging, it is a prime requirement to maintain high image quality in region of interest i.e diagnostically important regions. This work analyses a hybrid model of lossless compression in region of interest with high compression rate and lossy compression in other region. In this paper medical image is separated into two region, one is called NROI and other is called ROI. Region of interest part is compressed with ASPIHT algorithm and NROI part is compressed with the help of Block Truncation Coding algorithm. Our algorithm provide better PSNR and CR for medical images. KeywordsImage compression, WT (wavelet transform), db (Daubechies wavelet), BTC(Block Truncation Coding) SPIHT(Set Partitioning In Hierarchical Tree), ASPIHT(SPIHT using adaptive coding order), PSNR (Peak signal to noise ratio), Compression Ratio(CR), MSE(mean square error), region of interest(ROI)