Comparison Of Data Compression Schemes For Medical Images

Abstract

Medical images acquired and stored digitally continue to pose a major problem in the area of picture archiving and transmission. The need for accurate reproduction of such images, which constitute patient medical records, and the medico-legal problems of possible loss of information has led us to examine the suitability of data compression schemes for several different medical image modalities. We have examined both reversible coding and irreversible coding as methods of image for-matting and reproduction. In reversible coding we have tested run-length coding and arithmetic coding on image bit planes. In irreversible coding, we have studied transform coding, linear predictive coding, and block truncation coding and their effects on image quality versus compression ratio in several image modalities. In transform coding, we have applied discrete Fourier coding, discrete cosine coding, discrete sine transform, and Walsh-Hadamard transform to images in which a subset of the transformed coefficients were retained and quantized. In linear predictive coding, we used a fixed level quantizer. In the case of block truncation coding, the first and second moments were retained. Results of all types of irreversible coding for data compression were unsatisfactory in terms of reproduction of the original image. Run-length coding was useful on several bit planes of an image but not on others. Arithmetic coding was found to be completely reversible and resulted in up to 2 to 1 compression ratio.