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

70 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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