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.
Publication Date: 2023-12-14 PubMed ID: 38098240DOI: 10.1111/vru.13321Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
- Journal Article
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
Researcher Affiliations
- Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.
- Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.
- Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.
- Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.
- Clinical Unit of Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine, Vienna, Austria.
References
This article includes 38 references
- Dixon J, Biggi M, Weller R. Common artefacts and pitfalls in equine computed and digital radiography and how to avoid them. Equine Vet Educ 2018;30:326-335.
- Båth M, Håkansson M, Hansson J, Månsson LG. A conceptual optimisation strategy for radiography in a digital environment. Radiat Prot Dosim 2005;114:230-235.
- Lo WY, Puchalski SM. Digital image processing. Vet Radiol Ultrasound 2008; 49:S42-S47.
- Yamada S, Murase K. Effectiveness of flexible noise control image processing for digital portal images using computed radiography. Br J Radiol 2005;78:519-527.
- Prokop M, Neitzel U, Schaefer-Prokop C. Principles of image processing in digital chest radiography. J Thorac Imaging 2003;18:148-164.
- Don S, Whiting BR, Ellinwood JS, Foos DH, Kronemer KA, Kraus RA. Neonatal chest computed radiography: image processing and optimal image display. AJR Am J Roentgenol 2007;188:1138-1144.
- Ahn SY, Chae KJ, Goo JM. The potential role of grid-like software in bedside chest radiography in improving image quality and dose reduction: an observer preference study. Korean J Radiol 2018; 19:526-533.
- Precht H, Gerke O, Rosendahl K, Tingberg A, Waaler D. Digital radiography: optimization of image quality and dose using multi-frequency software. Pediatr Radiol 2012;42:1112-1118.
- Lo WY, Hornof WJ, Zwingenberger AL, Robertson ID. Multiscale image processing and antiscatter grids in digital radiography. Vet Radiol Ultrasound 2009;50:569-576.
- Shimbo G, Tagawa M, Matsumoto K, Tomihari M, Miyahara K. Effects of scatter correction processing on image quality of portable thoracic radiography in calves. Jpn J Vet Res 2018; 66:105-112.
- Kleinfelder TR, Curtis CK. Effects of Image postprocessing in digital radiography to detect wooden, soft tissue foreign bodies. Radiol Technol 2022;93:544-554.
- Whitlock J, Dixon J, Sherlock C, Tucker R, Bolt DM, Weller R. Technical innovation changes standard radiographic protocols in veterinary medicine: is it necessary to obtain two dorsoproximal-palmarodistal oblique views of the equine foot when using computerised radiography systems?. Vet Rec 2016;178:531.
- Thrall DE, Widmer WR. Textbook of Veterinary Diagnostic Radiology. 7th ed. Elsevier; 2018:986.
- Uffmann M, Schaefer-Prokop C. Digital radiography: the balance between image quality and required radiation dose. Eur J Radiol 2009;72:202-208.
- Precht H, Waaler D, Outzen CB. Does software optimization influence the radiologists' perception in low dose paediatric pelvic examinations?. Radiography 2019; 25:143-147.
- Lisson CG, Lisson CS, Kleiner S, Regier M, Beer M, Schmidt SA. Iterative scatter correction for grid-less skeletal radiography allows improved image quality equal to an antiscatter grid in adjunct with dose reduction: a visual grading study of 20 body donors. Acta Radiol 2019;60:735-741.
- Drost WT, Reese DJ, Hornof WJ. Digital radiography artifacts. Vet Radiol Ultrasound 2008;49:S48-56.
- Kawamura T, Naito S, Okano K, Yamada M. Improvement in image quality and workflow of X-ray examinations using a new image processing method, “Virtual Grid technology”. Fujifilm Res Dev 2015;60:21-27.
- Renger B, Brieskorn C, Toth V. Evaluation of dose reduction potentials of a novel scatter correction software for bedside chest X-ray imaging. Radiat Prot Dosim 2016;169:60-67.
- Tebrün W, Ludewig E, Köhler C, Böhme J, Pees M. Needle-based storage-phosphor detector radiography is superior to a conventional powder-based storage phosphor detector and a high-resolution screen-film system in small patients (budgerigars and mice). Sci Rep 2019;9:10057.
- Jadidi M, Båth M, Nyrén S. Dependency of image quality on acquisition protocol and image processing in chest tomosynthesis-a visual grading study based on clinical data. Br J Radiol 2018;91:20170683.
- Notohamiprodjo S, Roeper KM, Mueck FG. Advances in multiscale image processing and its effects on image quality in skeletal radiography. Sci Rep 2022;12:4726.
- Bochmann M, Ludewig E, Krautwald-Junghanns ME, Pees M. Comparison of the image quality of a high-resolution screen-film system and a digital flat panel detector system in avian radiography. Vet Radiol Ultrasound 2011;52:256-261.
- Moore CS, Liney GP, Beavis AW, Saunderson JR. A method to optimize the processing algorithm of a computed radiography system for chest radiography. Br J Radiol 2007;80:724-730.
- Díaz GM, López-Sanromán J, Weller R. A Practical Guide to Equine Radiography. 5M Publishing Ltd. Sheffield, UK. 2018:222.
- Precht H, Hansson J, Outzen C, Hogg P, Tingberg A. Radiographers' perspectives' on visual grading analysis as a scientific method to evaluate image quality. Radiography 2019;25:14-S18.
- Båth M, Månsson LG. Visual grading characteristics (VGC) analysis: a non-parametric rank-invariant statistical method for image quality evaluation. Br J Radiol 2007;80:169-176.
- Cohen J. A power primer. Psychol Bull 1992;112:155-159.
- Sasagawa T, Kunogi J, Masuyama S. New computed radiography processing condition for whole-spine radiography. Orthopedics 2011;34:906-910.
- Lisson CG, Lisson CS, Vogele D. Improvement of image quality applying iterative scatter correction for grid-less skeletal radiography in trauma room setting. Acta Radiol 2020;61:768-775.
- Decoster R, Mol H, Smits D. Post-processing, is it a burden or a blessing? Part 1 evaluation of clinical image quality. Radiography 2015;21:e1-e4.
- Sund P, Båth M, Kheddache S, Månsson LG. Comparison of visual grading analysis and determination of detective quantum efficiency for evaluating system performance in digital chest radiography. Eur Radiol 2004;14:48-58.
- Takahashi T, Ohara Y, Yamada M. Improving X-ray image quality based on human-body thickness and structure recognition. Fujifilm Res Dev 2017;62:30-37.
- Smet MH, Breysem L, Mussen E, Bosmans H, Marshall NW, Cockmartin L. Visual grading analysis of digital neonatal chest phantom X-ray images: impact of detector type, dose and image processing on image quality. Eur Radiol 2018;28:2951-2959.
- Willis CE, Slovis TL. The ALARA concept in pediatric CR and DR: dose reduction in pediatric radiographic exams-a white paper conference. AJR Am J Roentgenol 2005;184:373-374.
- Cerciello T, Bifulco P, Cesarelli M. Noise reduction in fluoroscopic image sequences for joint kinematics analysis. Paper presented at: XII Mediterranean Conference on Medical and Biological Engineering and Computing: MEDICON 2010, May 27-30, 2010, Chalkidiki, Greece.
- Bernhardt P, Lendl M, Deinzer F. New technologies to reduce pediatric radiation doses. Pediatr Radiol 2006;36:212-215.
- Keeble C, Baxter PD, Gislason-Lee AJ, Treadgold LA, Davies AG. Methods for the analysis of ordinal response data in medical image quality assessment. Br J Radiol 2016;89:20160094.
Citations
This article has been cited 0 times.Use Nutrition Calculator
Check if your horse's diet meets their nutrition requirements with our easy-to-use tool Check your horse's diet with our easy-to-use tool
Talk to a Nutritionist
Discuss your horse's feeding plan with our experts over a free phone consultation Discuss your horse's diet over a phone consultation
Submit Diet Evaluation
Get a customized feeding plan for your horse formulated by our equine nutritionists Get a custom feeding plan formulated by our nutritionists
