Abstract
The purpose of this article is to assess lossy image compression of digitized chest radiographs using radiologist assessment of anatomic structures and numerical measurements of image accuracy. Forty posterior-anterior (PA) chest radiographs were digitized and compressed using an irreversible wavelet technique at 10, 20, 40, and 80∶1. These were presented in a blinded fashion with an uncompressed image for A-B comparison of 11 anatomic structures as well as overall quality assessments. Mean error, root-mean square (RMS) error, maximum pixel error, and number of pixels within 1% of original value were also computed for compression ratios from 5∶1 to 80∶1. We found that at low compression (10∶1) there was a slight preference for compressed images. There was no significant difference at 20∶1 and 40∶1. There was a slight preference on some structures for the original compared with 80∶1 compressed images. Numerical measures showed high image faithfulness, both in terms of number of pixels that were within 1% of their original value, and by the average error for all pixels. Our findings suggest that lossy compression at 40∶1 or more can be used without perceptible loss in the representation of anatomic structures. On this finding, we will do a receiver-operator characteristic (ROC) analysis of nodule detection in lossy compressed images using 40∶1 compression.
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References
Aberle DR, Glesson F, Sayre JW, et al: The effect of irreversible image compression on diagnostic accuracy in thoracic imaging. Invest Radiol 28:398–403, 1993
Leger A, Omachi T, Wallace GK: JPEG still picture compression algorithm. Optical Eng 30:947–954, 1991
Wallace GK: The JPEG still picture compression standard. Commun Assoc Computing Machinery 34:30–44, 1991
Kostas TJ, Sullivan BJ, Ikeda M, et al: Clinical evaluation of irreversible image compression: analysis of chest imaging with computed radiography. Radiology 175:739–743, 1990
Mori T, Nakata H: Irreversible data compression in chest imaging using computed radiography: an evaluation. J Thorac Imaging 9:23–30, 1994
Goldberg MA, Pivovarov M, Mayo-Smith WW, et al: Application of wavelet compression to digital radiographs. AJR 163:463–468, 1994
Manduca A, Said A: Wavelet compression of medical images with set partitioning in hierarchical trees. Medical Imaging 1996: Image Display, Proc SPIE 2707 1996, pp 192–200
Swensen SJ, Gray JE, Brown LR, et al: A new asymmetric screen-film combination for conventional chest radiography: evaluation in 50 patients. AJR 160:483–486, 1993
Antonini M, Barlaud M, Mathieu P, et al: Image coding using wavelet transform. IEEE Trans Image Proc 1:205–220, 1992
Said A, Pearlman WA: A new fast and efficient image codec based on set partitioning in hierarchical trees. IEEE Trans Circuits and Systems for Video Tech 6:243–250, 1996
Donoho DI, Johnstone IM: Ideal denoising in an orthonormal basis chosen from a library of bases. Comptes Rendus Acad Sci 319:1317–1322, 1994
Lattner S, Good W, Maitz G: Visually weighted assessment of image degradation resulting from image compression. Proceedings of the SPIE, Medical Imaging, 1996, 11:59
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Erickson, B.J., Manduca, A., Persons, K.R. et al. Evaluation of irreversible compression of digitized posterior-anterior chest radiographs. J Digit Imaging 10, 97–102 (1997). https://doi.org/10.1007/BF03168595
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DOI: https://doi.org/10.1007/BF03168595