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 language | English |
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Pages (from-to) | 517-524 |
Number of pages | 8 |
Journal | Radiology |
Volume | 190 |
Issue number | 2 |
DOIs | |
State | Published - Feb 1994 |
Keywords
- Computed tomography (CT), image processing
- Data compression
- Images, interpretation
- Thorax, CT