APPLICATION OF WAVELET COMPRESSION TO DIGITIZED RADIOGRAPHS

OBJECTIVE. Image data compression is an enabling technology for telera diology and picture archive and communication systems. Compression dec reases the time and cost of image transmission and the requirements fo r image storage. Wavelets, discovered in 1987, constitute a new compre ssion technique that has been described in radiologic publications but , to our knowledge, no previous studies of its use have been reported. The purpose of this study was to demonstrate the application of wavel et-based compression technology to digitized radiographs. MATERIALS AN D METHODS. Twelve radiographs with abnormal findings were digitized, c ompressed, and decompressed by using a new wavelet-based lossy compres sion algorithm. Images were compressed at ratios from 10:1 to 60:1. Se ven board-certified radiologists reviewed images on a two-headed, high -resolution (2K x 2K) diagnostic workstation. Paired original and comp ressed/decompressed images were presented in random order. Reviewers a djusted contrast and magnification to judge whether image degradation was present, and if so, whether it was of diagnostic significance. Qua ntitative error measures were tabulated. RESULTS. Reviewers found no c linically relevant degradation below a compression ratio of 30:1. Skel etal radiographs appeared more sensitive to compression than did chest or abdominal radiographs, but the trend was not statistically signifi cant. Quantitative error measures increased gradually with compression ratio. CONCLUSION. On the basis of subjective assessment of image qua lity and the computational efficiency of the algorithm, wavelet-based techniques appear promising for the compression of digitized radiograp hs. The results of this initial experience can be used to design appro priate observer performance studies.