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A segmentation-based lossless image coding method for high-resolution medical image compression

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2 Author(s)
Liang Shen ; Array Syst. Comput. Inc., North York, Ont., Canada ; Rangayyan, R.M.

Lossless compression techniques are essential in archival and communication of medical images. Here, a new segmentation-based lossless image coding (SLIC) method is proposed, which is based on a simple but efficient region growing procedure. The embedded region growing procedure produces an adaptive scanning pattern for the image with the help of a very-few-bits-needed discontinuity index map. Along with this scanning pattern, an error image data part with a very small dynamic range is generated. Both the error image data and the discontinuity index map data parts are then encoded by the Joint Bi-level Image Experts Group (JBIG) method. The SLIC method resulted in, on the average, lossless compression to about 1.6 b/pixel from 8 b, and to about 2.9 b/pixel from 10 b with a database of ten high-resolution digitized chest and breast images. In comparison with direct coding by JBIG, Joint Photographic Experts Group (JPEG), hierarchical interpolation (HINT), and two-dimensional Burg prediction plus Huffman error coding methods, the SLIC method performed better by 4% to 28% on the database used.

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Medical Imaging, IEEE Transactions on  (Volume:16 ,  Issue: 3 )