Comparison of image compression viability for lossy and lossless JPEG and Wavelet data reduction in coronary angiography

Int J Cardiovasc Imaging. 2001 Feb;17(1):1-12. doi: 10.1023/a:1010644318298.

Abstract

Background: Lossless or lossy compression of coronary angiogram data can reduce the enormous amounts of data generated by coronary angiographic imaging. The recent International Study of Angiographic Data Compression (ISAC) assessed the clinical viability of lossy Joint Photographic Expert Group (JPEG) compression but was unable to resolve two related questions: (A) the performance of lossless modes of compression in coronary angiography and (B) the performance of newer lossy wavelet algorithms. This present study seeks to supply some of this information.

Methods: The performance of several lossless image compression methods was measured in the same set of images as used in the ISAC study. For the assessment of the relative image quality of lossy JPEG and wavelet compression, the observers ranked the perceived image quality of computer-generated coronary angiograms compressed with wavelet compression relative to the same images with JPEG compression. This ranking allowed the matching of compression ratios for wavelet compression with the clinically viable compression ratios for the JPEG method as obtained in the ISAC study.

Results: The best lossless compression scheme (LOCO-I) offered a mean compression ratio (CR) of 3.80:1. The quality of images compressed with the lossy wavelet-based method at CR = 10:1 and 20:1 was comparable to JPEG compression at CR = 6:1 and 10:1, respectively.

Conclusion: The study has shown that lossless compression can exceed the CR of 2:1 usually quoted. For lossy compression, the range of clinically viable compression ratios can probably be extended by 50 to 100% when applying wavelet compression algorithms as compared to JPEG compression. These results can motivate a larger clinical study.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Coronary Angiography*
  • Coronary Disease / diagnostic imaging*
  • Humans
  • Image Processing, Computer-Assisted*
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted*