Lossy image compression for digital medical imaging systems

Paul S. Wilhelm; David R. Haynor; Yongmin Kim; Eve A. Riskin

doi:10.1117/12.55970

1 October 1991 Lossy image compression for digital medical imaging systems

Paul S. Wilhelm, David R. Haynor, Yongmin Kim, Eve A. Riskin

Author Affiliations +

Optical Engineering, Vol. 30, Issue 10, (October 1991). https://doi.org/10.1117/12.55970

Abstract

Image compression at rates oflO:1 orgreatercould make picture archiving and communication systems (PACS) much more responsive and economically attractive. A protocol is described for subjective and objective evaluation of the fidelity of compressed/decompressed images compared to originals. The results of its application to four representative and promising compression methods are presented. The four compression methods examined are predictive pruned tree-structured vector quantization, fractal compression, the full-frame discrete cosine transform with equal weighting of block bit allocation, and the full-frame discrete cosine transform with human visual system weighting of block bit allocation. A protocol was developed for side-by-side observer comparison of reconstructed images with originals. Three 1024 x 1024 computed radiography (CR) images andtwo 512 x 512 x-ray computed tomography(CT) images were viewed at six bit rates by nine radiologists at the University of Washington Medical Center. The radiologists' subjective evaluations of image fidelity were compared to calculations of mean square error for each decompressed image.

Citation Download Citation

Paul S. Wilhelm, David R. Haynor, Yongmin Kim, and Eve A. Riskin "Lossy image compression for digital medical imaging systems," Optical Engineering 30(10), (1 October 1991). https://doi.org/10.1117/12.55970

Published: 1 October 1991

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