E-ISSN: 1305-3612
The impact of irreversible image data compression on post-processing algorithms in computed tomography
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General Radiology - Original Article
VOLUME: 26 ISSUE: 1
P: 22-27
January 2020

The impact of irreversible image data compression on post-processing algorithms in computed tomography

Diagn Interv Radiol 2020;26(1):22-27
DOI: 10.5152/dir.2019.18245
Daniel Pinto dos Santos 1,2
Conrad Friese 2,3
Jan Borggrefe 1
Peter Mildenberger 2
Aline Mähringer-Kunz 2
Roman Kloeckner 2
1. Department of Radiology, University Hospital Cologne, Cologne, Germany
2. Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
3. Department of Internal Medicine, St. Hildegardis Hospital, Cologne, Germany
No information available.
No information available
Received Date: 27.12.2018
Accepted Date: 21.06.2019
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ABSTRACT

PURPOSE

We aimed to evaluate the influence of irreversible image compression at varying levels on image post-processing algorithms (3D volume rendering of angiographs, computer-assisted detection of lung nodules, segmentation and volumetry of liver lesions, and automated evaluation of functional cardiac imaging) in computed tomography (CT).

METHODS

Uncompressed CT image data (30 angiographs of the lower limbs, 38 lung exams, 20 liver exams and 30 cardiac exams) were anonymized and subsequently compressed using the JPEG2000 algorithm with compression ratios of 8:1, 10:1, and 15:1. Volume renderings of CT angiographies obtained from compressed and uncompressed data were compared using objective and subjective measures. Computer-assisted detection of lung nodules was performed on compressed and uncompressed image data and compared with respect to diagnostic performance. Segmentation and volumetry of liver lesions as well as measurement of ejection fraction on cardiac studies was performed on compressed and uncompressed datasets; differences in measurements were analyzed.

RESULTS

No differences could be detected for the 3D volume renderings and no statistically significant differences in performance were found for the computer-assisted detection algorithm. Measurements in volumetry of liver lesions and functional cardiac imaging showed good to excellent reliability.

CONCLUSION

Irreversible image compression within the limits proposed by the European Society of Radiology has no significant influence on commonly used image post-processing algorithms in CT.