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Near-lossless compression of medical images through entropy-coded DPCM

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2 Author(s)
K. Chen ; Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA, USA ; T. V. Ramabadran

The near-lossless, i.e., lossy but high-fidelity, compression of medical Images using the entropy-coded DPCM method is investigated. A source model with multiple contexts and arithmetic coding are used to enhance the compression performance of the method. In implementing the method, two different quantizers each with a large number of quantization levels are considered. Experiments involving several MR (magnetic resonance) and US (ultrasound) images show that the entropy-coded DPCM method can provide compression in the range from 4 to 10 with a peak SNR of about 50 dB for 8-bit medical images. The use of multiple contexts is found to improve the compression performance by about 25% to 30% for MR images and 30% to 35% for US images. A comparison with the JPEG standard reveals that the entropy-coded DPCM method can provide about 7 to 8 dB higher SNR for the same compression performance

Published in:

IEEE Transactions on Medical Imaging  (Volume:13 ,  Issue: 3 )