Lossy (15:1) JPEG compression of digital coronary angiograms does not limit detection of subtle morphological features

Circulation. 1997 Aug 19;96(4):1157-64. doi: 10.1161/01.cir.96.4.1157.

Abstract

Background: Development of the "all-digital" cardiac catheterization laboratory has been slowed by substantial computer archival and transfer requirements. Lossy data compression reduces this burden but creates irreversible changes in images, potentially impairing detection of clinically important angiographic features.

Methods and results: Fifty image sequences from 31 interventional procedures were viewed both in the original (uncompressed) state and after 15:1 lossy Joint Photographic Expert's Group (JPEG) compression. Experienced angiographers identified dissections, suspected thrombi, and coronary stents, and their results were compared with those from a consensus panel that served as a "gold standard." The panel and the individual observers reviewed the same image sequences 4 months after the first session to determine intraobserver variability. Intraobserver agreement for original images was not significantly different from that for compressed images (89.8% versus 89.5% for 600 pairs of observations in each group). Agreement of individual observers with the consensus panel was not significantly different for original images from that for compressed images (87.6% versus 87.3%; CIs for the difference, -4.0%, 4.0%). Subgroup analysis for each observer and for each detection task (dissection, suspected thrombus, and stent) revealed no significant difference in agreement.

Conclusions: The identification of dissections, thrombi, and coronary stents is not substantially impaired by the application of 15:1 lossy JPEG compression to digital coronary angiograms. These data suggest that digital angiographic images compressed in this manner are acceptable for clinical decision-making.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Coronary Angiography / methods*
  • Humans
  • Observer Variation
  • Radiographic Image Enhancement*
  • Radiology Information Systems
  • Signal Processing, Computer-Assisted*