Improved compressibility of multislice CT datasets using 3D JPEG2000 compression

Khan M. Siddiqui, Eliot L. Siegel, Bruce I. Reiner, Olivier Crave, Jeffrey P. Johnson, Zhenyu Wu, Joseph C. Dagher, Ali Bilgin, Michael W. Marcellin, Mariappan Nadar

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


This study evaluated the compressibility of multislice CT (MSCT) datasets and its dependence on (1) slice thickness and (2) the use of three-dimensional (3D) vs. 2D JPEG2000 compression methods. Five thoracic CT datasets were obtained using a 16-detector MSCT scanner with a collimation of 0.75 mm (120 kVp, 90 mAs) and reconstructed at five slice thicknesses from 0.75 to 10.0 mm. These datasets were irreversibly compressed using a standard 2D JPEG2000 encoder and a developmental 3D JPEG2000 algorithm based on Part 2 of the JPEG2000 standard. Compression ratios ranged from 4:1 to 64:1. Image distortion was computed utilizing peak signal-to-noise ratio (PSNR) and the Sarnoff JNDmetrix visual discrimination model. For 2D compression, the thinnest sections were substantially less compressible than thicker sections for the same level of image quality, particularly at higher compression ratios. Applying 3D compression yielded consistently higher image quality in most cases compared to 2D compression at the same ratios. The advantage of 3D compression increased for thinner slices and higher compression ratios. These results indicate that 3D JPEG2000 (Part 2) compression offers substantial advantages over the current 2D JPEG2000 standard, yielding better quantitative image quality at similar compression ratios or comparable image quality at higher compression ratios.

Original languageEnglish (US)
Pages (from-to)57-62
Number of pages6
JournalInternational Congress Series
Issue numberC
StatePublished - Jun 1 2004


  • 3D compression
  • Image compression
  • JPEG2000
  • Just noticeable difference (JND)
  • Multislice CT
  • Slice thickness
  • Visual discrimination model

ASJC Scopus subject areas

  • Medicine(all)


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