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.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
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
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
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
Issue Date:
DOI: https://doi.org/10.1007/BF03168595