Title (eng)
Image processing setting adaptions according to image dose and radiologist preference can improve image quality in computed radiography of the equine distal limb: A cadaveric study
Author
Abstract (eng)
Image processing (IP) in digital radiography has been steadily refined to improve image quality. Adaptable settings enable users to adjust systems to their specific requirements. This prospective, analytical study aimed to investigate the influence of different IP settings and dose reductions on image quality. Included were 20 cadaveric equine limb specimens distal to the metacarpophalangeal and metatarsophalangeal joints. Images were processed with the Dynamic Visualization II system (Fujifilm) using five different IP settings including multiobjective frequency processing, flexible noise control (FNC), and virtual grid processing (VGP). Seven criteria were assessed by three veterinary radiology Diplomates and one veterinary radiology resident in a blinded study using a scoring system. Algorithm comparison was performed using an absolute visual grading analysis. The rating of bone structures was improved by VGP at full dose (P < .05; AUCVGC = 0.45). Überschwinger artifact perception was enhanced by VGP (P < .001; AUCVGC = 0.66), whereas image noise perception was suppressed by FNC (P < .001; AUCVGC = 0.29). The ratings of bone structures were improved by FNC at 50% dose (P < .05; AUCVGC = 0.44), and 25% dose (P < .001; AUCVGC = 0.32), and clinically acceptable image quality was maintained at 50% dose (mean rating 2.16; 95.8% ratings sufficient or better). The favored IP setting varied among observers, with higher agreement at lower dose levels. These findings supported using individualized IP settings based on the radiologist's preferences and situational image requirements, rather than using default settings.
Keywords (eng)
Visual Grading AnalysisDigital RadiographyReductionSystemOptimizationSoftware
Type (eng)
Language
[eng]
Persistent identifier
Is in series
Title (eng)
Veterinary Radiology & Ultrasound
Volume
65
Issue
1
ISSN
1740-8261
Issued
2024
Number of pages
12
Publication
Wiley
Version type (eng)
Date issued
2024
Access rights (eng)
License
Rights statement (eng)
© 2023 The Authors
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