The impact of irreversible image data compression on post-processing algorithms in computed tomography.
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 car...
| Published in: | Diagnostic & Interventional Radiology Vol. 26; no. 1; pp. 22 - 28 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Published: |
Galenos Yayinevi Tic. LTD. STI
Jan/Feb2020
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=141041431&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 141041431 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13053825 39NM jtl: Diagnostic & Interventional Radiology issn: 13053825 maglogo: N pubinfo: dt: Jan/Feb2020 vid: 26 iid: 1 pid: 28155 pub: Galenos Yayinevi Tic. LTD. STI artinfo: ui: 141041431 141041431 NLM31904569 10.5152/dir.2019.18245 NLM31904569 141041431 ppf: 22 ppct: 6 formats: fmt: @attributes: type: P tig: atl: The impact of irreversible image data compression on post-processing algorithms in computed tomography. aug: au: dos Santos, Daniel Pinto Friese, Conrad Borggrefe, Jan Mildenberger, Peter Mähringer-Kunz, Aline Kloeckner, Roman Santos, Daniel Pinto Dos affil: Department of Radiology, University Hospital Cologne, Cologne, Germany sug: subj: Image Processing, Computer Assisted Methods Lung Anatomy and Histology Tomography, X-Ray Computed Methods Extremities Anatomy and Histology Heart Anatomy and Histology Liver Anatomy and Histology Retrospective Design Reproducibility of Results Clinical Assessment Tools Impact of Events Scale ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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