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Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association2023; doi: 10.1111/vru.13321

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.

Abstract: 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; AUC  = 0.45). Überschwinger artifact perception was enhanced by VGP (P < .001; AUC  = 0.66), whereas image noise perception was suppressed by FNC (P < .001; AUC  = 0.29). The ratings of bone structures were improved by FNC at 50% dose (P < .05; AUC  = 0.44), and 25% dose (P < .001; AUC  = 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.
© 2023 The Authors. Veterinary Radiology & Ultrasound published by Wiley Periodicals LLC on behalf of American College of Veterinary Radiology.
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Publication Date: 2023-12-14 PubMed ID: 38098240DOI: 10.1111/vru.13321Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research article is about image processing refinement in digital radiography, focusing on how adjusting settings and reductions in dosage can affect image quality, specifically in cadaveric studies of the “equine distal limb”, a part of a horse’s lower leg.

Overview of the Research

The study explored how adjusting settings in digital radiography, along with variations in radiation dosage, can influence image quality. This was achieved by assessing 20 cadaveric “equine distal limb” specimens. A type of image processing software, the Dynamic Visualization II system, made by Fujifilm, was used with five different settings, including multiobjective frequency processing, flexible noise control, and virtual grid processing.

  • The Advanced Visualization II system is designed to aid in refining images in radiography, a diagnostic procedure that involves the use of radiant energy, such as X-rays.
  • Multiobjective frequency processing is a noise reducing algorithm or technique in imaging.
  • Flexible noise control refers to an adaptable feature that allows for the control of image noise and texture. Noise in this context refers to the random grainy splotches often seen in lesser quality photos.
  • Virtual grid processing is a feature designed to reduce scattered radiation artifacts in radiographic images. This improves the image contrast and clarity by reducing unwanted noise from scatter radiation.

Evaluation and Results

The images were assessed based on seven different criteria by four specialists in veterinary radiology. The methods and analysis of the results were blinded, meaning that the researchers did not know which images were associated with which settings or doses during their assessment.

The results showed that:

  • The rating of bone structures was improved by using the virtual grid processing (VGP) tool at full radiation dose
  • The perception of Überschwinger artifacts, abrupt changes in brightness in digital images, was enhanced by VGP
  • The perception of image noise was suppressed by flexible noise control (FNC)
  • The ratings of bone structures were improved by using FNC at both 50% radiation dose and 25% radiation dose
  • Clinically acceptable image quality was maintained even when the radiation dose was reduced by half
  • The radiologists had varying preferences for image processing settings, but agreed more consistently when the radiation dose was lower

Conclusion

The findings of the study suggest that the use of adaptive image processing settings, tailored to both the radiologist’s preferences and specific image requirements, can improve the quality of radiographic images instead of purely relying on default settings. The ability to reduce the radiation dose used without compromising image quality further underpins the potential of these adaptable systems in enhancing clinical radiography.

Cite This Article

APA
Seeber M, Lederer KA, Rowan C, Strohmayer C, Ludewig E. (2023). 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. Vet Radiol Ultrasound. https://doi.org/10.1111/vru.13321

Publication

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
ISSN: 1740-8261
NlmUniqueID: 9209635
Country: England
Language: English

Researcher Affiliations

Seeber, Matthias
  • Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.
Lederer, Kristina A
  • Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.
Rowan, Conor
  • Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.
Strohmayer, Carina
  • Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.
Ludewig, Eberhard
  • Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.

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