Hybrid Lossless Coder of Medical Images with Statistical Data Modelling
Methods of lossless compression of medical image data are considered in this paper. Chosen classes of efficient algorithms were constructed, examined and optimised to conclude the most useful tools for creation of medical image representation. 2-D context-based prediction schemes, and statistical models of entropy coder were fitted to different characteristics of US, MR and CT images. The SSM technique of suitable-to-image characteristics scanning followed by statistical modelling of the context in arithmetic coder was found out as the most effective in most cases. Average bit rate value over test images is equal to 2.54 bpp for SSM coder and significantly overcomes 2.92 bpp achieved for CALIC. Efficient hybrid encoding method (SHEC) was proposed as a complex tool for medical image archiving and transmission. SHEC develops SSM by including CALIC-like coder for archiving the highest quality images and JPEG2000-like wavelet coder for transmission of high and middle quality images in telemedicine systems.
Keywordsmedical image compression reversible hybrid coders statistical modeling
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