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Quantitative analysis of effects of the grid specifications on the quality of digital radiography images

  • Sanghyun LeeEmail author
  • Woohyun Chung
Scientific Paper
  • 3 Downloads

Abstract

A grid is one of the key components of a digital radiography (DR) system because it removes scattered radiation, which arises when X-rays penetrate an object and improves diagnostic accuracy by enhancing image quality. With the widespread use of DR systems, demand for grids with high precision has simultaneously increased. Because unsuitable grids may decrease image quality and lead to misdiagnosis, using optimised grids for DR systems is critical. In this study, we aimed to analyse the quality of X-ray images acquired using grids with different specifications and proposed standardised criteria for grid use on the basis of our results. We measured modulation transfer function (MTF), normalised noise power spectrum (NNPS) and detective quantum efficiency (DQE) using grids with different ratios (10:1, 12:1 and 15:1) with or without implementing poly methyl methacrylate (PMMA) phantoms (0–20 cm). Pixel pitch of the detector used in this experiment was 143 μm. Based on this, a grid with a line frequency of 85 line pairs/cm was selected to prevent distortion caused by implementing unoptimised grids. As a result, the NNPS was found to increase when using the grid, and the difference in MTF and DQE was only measured when the scattered X-ray was generated by stacking the PMMA phantom. However, grids showed a positive effect MTF and DQE when the PMMA phantom was implemented. Specifically, MTF and DQE improved with increase in grid ratio. Thus, it is desirable to use a high-ratio grid to improve image quality.

Keywords

Digital radiography Grid Grid ratio Modulation transfer function Detective quantum efficiency Normalised noise power spectrum 

Notes

Compliance with ethical standards

Conflict of interest

The authors of this manuscript declare relationships with JPI Healthcare, Co., Ltd., and the authors state that this work has not received any funding.

Research involving human participants and/or animals

We did not perform direct experiments on humans or animals. Results of prior human radiological studies were selected.

Informed consent

Informed consent was obtained from all participants in the study.

References

  1. 1.
    Bucky G (1913) A grating-diaphragm to cut off secondary rays from the object. Arch Roentgen Ray 18:6–9.  https://doi.org/10.1259/arr.1913.0005 CrossRefGoogle Scholar
  2. 2.
    Hondius Boldingh W (1964) Grids to reduce scattered X-rays in medical radiography. Technische Hogeschool Eindhoven, Eindhoven.  https://doi.org/10.6100/IR62689 Google Scholar
  3. 3.
    Tang C-M, Stier E, Fischer K, Guckel H (1998) Anti-scattering X-ray grid. Microsyst Technol 4:187–192.  https://doi.org/10.1007/s005420050128 CrossRefGoogle Scholar
  4. 4.
    Hendee William R, Russell Ritenour E (2002) Medical imaging physics. Radiography, 4th edn. Wiley, New York, pp 217–234Google Scholar
  5. 5.
    Belykh I (2014) Grid artifacts suppression in computed radiographic images. Int J Biomed Biol Eng 8:1402–1405Google Scholar
  6. 6.
    Papp Jeffrey (2014) Quality management in the imaging sciences, 5th edn. Elsevier, MarylandGoogle Scholar
  7. 7.
    Yoon Jai-Woong, Park Young-Guk, Park Chun-Joo, Kim Do-Il, Lee Jin-Ho, Chung Nag-Kun, Choe Bo-Young, Suh Tae-Suk, Lee Hyoung-Koo (2007) Reduction of a grid moiré pattern by integrating a carbon-interspaced high precision X-ray grid with a digital radiographic detector. Med Phys 34:4092–4097.  https://doi.org/10.1118/1.2775743 CrossRefGoogle Scholar
  8. 8.
    Belykh I, Cornelius CW (2001) Antiscatter stationary-grid artifacts automated detection and removal in projection radiography images. In: Proceedings of the SPIE 4322, Medical imaging 2001: Image processing, pp 1162–1166  https://doi.org/10.1117/12.430992
  9. 9.
    International Electrotechnical Commission (2013) IEC 60627:2013, Diagnostic X-ray imaging equipment: characteristics of general purpose and mammographic anti-scatter grids, 3rd edn. International Electrotechnical Commission, GenevaGoogle Scholar
  10. 10.
    JPI Healthcare (2015) JPI’s grid book, 7th edn. JPI Healthcare, Ansan-siGoogle Scholar
  11. 11.
    Khodajou-Chokami H, Sohrabpour M (2015) Design of linear anti-scatter grid geometry with optimum performance for screen-film and digital mammography systems. Phys Med Biol 60:5753–5766.  https://doi.org/10.1088/0031-9155/60/15/5753 CrossRefGoogle Scholar
  12. 12.
    Ghaffarian P, Sharafi AA, Keshavarz K, Zaidi H (2005) MCNP4C-based Monte Carlo study of grid performance in diagnostic radiology. Biomed Tech 50:1098–1099Google Scholar
  13. 13.
    Woo-HyunChung Sang-HyunLee (2018) Study of Monte Carlo simulator for estimation of anti-scatter grid physical characteristics on IEC 60627:2013-based. Am J Phys Appl 6:35–42.  https://doi.org/10.11648/j.ajpa.20180602.12 Google Scholar
  14. 14.
    Kenneth L, Bontrager MA, Lampignano J (2013) Textbook of radiographic positioning and related anatomy, 8th edn. Elsevier, MarylandGoogle Scholar
  15. 15.
    International Electrotechnical Commission (2003) IEC62220-1:2003, Medical electrical equipment – Characteristics of digital X-ray imaging devices – Part 1: determination of the detective quantum efficiency, 1st edn. International Electrotechnical Commission, GenevaGoogle Scholar
  16. 16.
    Neitzel Ulrich, Buhr Egbert, Hilgers Gerhard, Granfors Paul R (2004) Determination of the modulation transfer function using the edge method: influence of scattered radiation. Med Phys 31:3485–3491.  https://doi.org/10.1118/1.1813872 CrossRefGoogle Scholar
  17. 17.
    Samei Ehsan, Flynn Michael J (2003) An experimental comparison of detector performance for direct and indirect digital radiography systems. Med Phys 30:608–622.  https://doi.org/10.1118/1.1561285 CrossRefGoogle Scholar
  18. 18.
    Samei Ehsan, Flynn Michael J, Reimann David A (1998) A method for measuring the presampled MTF of digital radiographic systems using an edge test device. Med Phys 25:102–113.  https://doi.org/10.1118/1.598165 CrossRefGoogle Scholar
  19. 19.
    Gupta Arun Kumar, Chowdhury Veena, Khandelwal Niranjan (2013) Diagnostic radiology: recent advances and applied physics in imaging, 2nd edn. Jaypee Brothers Medical Pub, New DelhiCrossRefGoogle Scholar
  20. 20.
    Van Metter Richard L, Beutel Jacob, Kundel Harold L (2000) Handbook of medical imaging volume 1 physics and psychophysics. Applied linear-systems theory. SPIE Press, Bellingham, pp 79–160Google Scholar
  21. 21.
    Ranger NT, Samei E, Dobbins JT 3rd, Ravin CE (2007) Assessment of detective quantum efficiency: intercomparison of a recently introduced international standard with prior methods. Radiology 243:785–795.  https://doi.org/10.1148/radiol.2433060485 CrossRefGoogle Scholar
  22. 22.
    Zhou Zhongxing, Gao Feng, Zhao Huijuan, Zhang Lixin (2011) Techniques to improve the accuracy of noise power spectrum measurements in digital X-ray imaging based on background trends removal. Med Phys 38:1600–1610.  https://doi.org/10.1118/1.3556566 CrossRefGoogle Scholar
  23. 23.
    Williams Mark B, Mangiafico Peter A, Simoni Piero U (1999) Noise power spectra of images from digital mammography detectors. Med Phys 26:1279–1293.  https://doi.org/10.1118/1.598623 CrossRefGoogle Scholar
  24. 24.
    Dong Sik Kim (2016) Noise power spectrum measurements in digital imaging with gain nonuniformity correction. IEEE 25:3712–3722.  https://doi.org/10.1109/TIP.2016.2574985 Google Scholar

Copyright information

© Australasian College of Physical Scientists and Engineers in Medicine 2019

Authors and Affiliations

  1. 1.R&D, JPI Healthcare, Co., Ltd.Ansan-siRepublic of Korea

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