Thoracic CT images: Effect of lossy image compression on diagnostic accuracy

  • Pamela C. Cosman
  • , H. Christian Davidson
  • , Colleen J. Bergin
  • , Chien Wen Tseng
  • , Lincoln E. Moses
  • , Eve A. Riskin
  • , Richard A. Olshen
  • , Robert M. Gray

Research output: Contribution to journalArticlepeer-review

72 Scopus citations

Abstract

PURPOSE: To evaluate the effects of lossy image (noninvertible) compression on diagnostic accuracy of thoracic computed tomographic images. MATERIALS AND METHODS: Sixty images from patients with mediastinal adenopathy and pulmonary nodules were compressed to six different levels with tree- structured vector quantization. Three radiologists then used the original and compressed images for diagnosis. Unlike many previous receiver operating characteristic-based studies that used confidence rankings and binary detection tasks, this study examined the sensitivity and predictive value positive scores from nonbinary detection tasks. RESULTS: At the 5% significance level, there was no statistically significant difference in diagnostic accuracy of image assessment at compression rates of up to 9:1. CONCLUSION: The techniques presented for evaluation of image quality do not depend on the specific compression algorithm and provide a useful approach to evaluation of the benefits of any lossy image processing technique.

Original languageEnglish
Pages (from-to)517-524
Number of pages8
JournalRadiology
Volume190
Issue number2
DOIs
StatePublished - Feb 1994

Keywords

  • Computed tomography (CT), image processing
  • Data compression
  • Images, interpretation
  • Thorax, CT

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