Journal of Digital Imaging

, 10:97

Evaluation of irreversible compression of digitized posterior-anterior chest radiographs


  • Bradley J. Erickson
    • Department of RadiologyMayo Clinic
  • Armando Manduca
    • Department of RadiologyMayo Clinic
  • Kenneth R. Persons
    • Department of RadiologyMayo Clinic
  • Frank Earnest
    • Department of RadiologyMayo Clinic
  • Thomas E. Hartman
    • Department of RadiologyMayo Clinic
  • Gordon F. Harms
    • Department of RadiologyMayo Clinic
  • Larry R. Brown
    • Department of RadiologyMayo Clinic

DOI: 10.1007/BF03168595

Cite this article as:
Erickson, B.J., Manduca, A., Persons, K.R. et al. J Digit Imaging (1997) 10: 97. doi:10.1007/BF03168595


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.

Key Words

data compressionpicture archiving and communications system

Copyright information

© Society for Imaging Informatics in Medicine 1997