Advertisement

Russian Journal of Nondestructive Testing

, Volume 54, Issue 11, pp 797–810 | Cite as

Selecting Parameters of Detectors When Recognizing Materials Based on the Separation of Soft and Hard X-Ray Components

  • S. P. Osipov
  • E. Yu. Usachev
  • S. V. ChakhlovEmail author
  • S. A. Shchetinkin
  • E. N. Kamysheva
Radiation Methods
  • 16 Downloads

Abstract

An approach to choosing the materials and thicknesses of detectors and an intermediate filter is considered in a material recognition method based on single X-raying of a test object with separate detection of soft and hard photons. The approach combines the maximum sensitivity to changes in the effective atomic number and the minimum error of its estimation. An example is given of selecting the parameters of the detectors and intermediate filter for X-ray energies in the range from 100 to 300 keV.

Keywords

X-ray radiation inspection control effective atomic number material recognition dualenergy method 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Treeaporn, V. and Neifeld, M.A., Detection with polychromatic X-ray pencil beam illumination: information theoretic bounds, Appl. Opt., 2018, vol. 57, no. 9, pp. 1977–1992.CrossRefGoogle Scholar
  2. 2.
    Rogers, T.W., Jaccard, N., Morton, E.J., and Griffin, L.D., Automated X-ray image analysis for cargo security: Critical review and future promise, J. X-Ray Sci. Technol., 2017, vol. 25, no. 1, pp. 33–56.CrossRefGoogle Scholar
  3. 3.
    Duvillier, J., Dierick, M., Dhaene, J., Van Loo, D., Masschaele, B., Geurts, R., Hoorebeke, L.V., and Boone, M.N., Inline multi-material identification via energy radiographic measurements, NDT & E Int., vol. 94, pp. 120–125.Google Scholar
  4. 4.
    Linev, L., Lineva, E., Pozdnyakov, D., Emelianov, I., and Sosenko, K., Portal monitoring devices, Eng. Scintill. Mater. Radiat. Technol.: Proc. ISMART 2016, 2017, vol. 200, pp. 325–338.CrossRefGoogle Scholar
  5. 5.
    Karoly, S., Technologies to counter aviation security threats, AIP Conf. Proc., AIP Publishing, 2017, vol. 1898, no. 1, article 050002.CrossRefGoogle Scholar
  6. 6.
    Chen, G., Bennett, G., and Perticone, D., X-ray radiography for automatic high-Z material detection, Nucl. Instrum. Methods Phys. Res., Sect. B, 2007, vol. 261, nos. 1–2, pp. 356–359.CrossRefGoogle Scholar
  7. 7.
    Osipov, S.P., Udod, V.A., and Wang, Y., Identification of materials in X-ray inspections of objects by the dualenergy method, Russ. J. Nondestr. Test., 2017, vol. 53, no. 8, pp. 568–587.CrossRefGoogle Scholar
  8. 8.
    Dmitruk, K., Mazur, M., Denkowski, M., and Mikolajczak, P., Method for filling and sharpening X-ray images, IFAC-PapersOnLine, 2015, vol. 48, no. 4, pp. 342–347.CrossRefGoogle Scholar
  9. 9.
    Klimenov, V.A., Temnik, A.K., and Osipov, S.P., Identification of the substance of a test object using the dualenergy method, Russ. J. Nondestr. Test., 2013, vol. 49, no. 11, pp. 642–649.CrossRefGoogle Scholar
  10. 10.
    Bonnin, A., Duvauchelle, P., Kaftandjian, V., and Ponard, P., X-ray ray computed tomography. Concept of effective atomic number, Nucl. Instrum. Methods Phys. Res., Sect. B, 2014, vol. 318, pp. 223–231.CrossRefGoogle Scholar
  11. 11.
    Shi, X. Improving object classification in X-ray luggage inspection, Ph. D. Dissertation, Virginia Polytech. Inst. State Univ., February 2000. URL: http://hdl.handle.net/10919/28389Google Scholar
  12. 12.
    Rebuffel, V. and Dinten, J.M., Dual-energy X-ray imaging: benefits and limits, Insight Nondestr. Test. Cond. Monit., 2007, vol. 49, no. 10, pp. 589–594.CrossRefGoogle Scholar
  13. 13.
    Runkle, R.C., White, T.A., Miller, E.A., Caggiano, J.A., and Collins, B.A., Photon and neutron interrogation detection in air cargo: A critical review, Nucl. Instrum. Methods Phys. Res., Sect. A, 2009, vol. 603, no. 3, pp. 510–528.CrossRefGoogle Scholar
  14. 14.
    Brooks, R.A. and Di Chiro, G., Split-detector computed tomography: a preliminary report, Radiology, 1978, vol. 126, pp. 255–257.CrossRefGoogle Scholar
  15. 15.
    Barnes, G.T., Sones, R.A., Tesic, M.M., Morgan, D.R., and Sanders, J.N., Detector for dual-energy digital radiography, Radiology, 1985, vol. 156, no. 2, pp. 537–540.CrossRefGoogle Scholar
  16. 16.
    Fredenberg, E., Spectral and dual-energy X-ray imaging for medical applications, Nucl. Instrum. Phys. Res., Sect. A, 2018, vol. 878, pp. 74–87.CrossRefGoogle Scholar
  17. 17.
    Koukou, V., Martini, N., Michail, C., Sotiropoulou, P., Fountzoula, C., Kalyvas, N., Kandarakis, I., Nikiforidis, G., and Fountos, G., Dual energy method for breast imaging: a simulation study, Comput. Math. Methods Med., 2015, vol. 2015, article ID 574238. http://dx.doi.org/ doi 10.1155/2015/574238Google Scholar
  18. 18.
    Zavyalkin, F.M. and Osipov, S.P., Dependence of the average value and fluctuations of absorbed energy on the size of scintillator, At. Energ., 1985, vol. 59, no. 4, pp. 281–283.Google Scholar
  19. 19.
    Udod, V.A., Osipov, S.P., and Wang, Y., The mathematical model of image generated by scanning digital radiography system, IOP Conf. Ser.: Mater. Sci. Eng., IOP Publishing, 2017, vol. 168, no. 1, article ID 012042.Google Scholar
  20. 20.
    Van Loef, E.V.D., Dorenbos, L.P., Van Eijk, C.W.E., Kramer, K., and Gudel, H.U., Scintillation properties of LaCl/sub 3: Ce/sup 3/crystals: fast, efficient, and high-energy resolution scintillators, IEEE Trans. Nucl. Sci., 2001, vol. 48, no. 3, pp. 341–345.CrossRefGoogle Scholar
  21. 21.
    Badano, A., Optical blur and collection efficiency in columnar phosphors for x-ray imaging, Nucl. Instrum. Methods Phys. Res., Sect. A, 2003, vol. 508, pp. 467–479.CrossRefGoogle Scholar
  22. 22.
    Watanabe, S., Hybrid manipulations for the solution of systems of nonlinear algebraic equations, Publ. Res. Inst. Math. Sc., 1983, vol. 19, no. 2, pp. 367–395.CrossRefGoogle Scholar
  23. 23.
    Alvarez, R.E. and Macovski, A., Energy-selective reconstructions in x-ray computerized tomography, Phys. Med., vol. 21, no. 5, pp. 733–744.Google Scholar
  24. 24.
    Brandis, M., Development of gamma-ray detector for Z-selective radiographic imaging, Ph. D. Dissertation, Hebrew Univ. Jerusalem, 2013.Google Scholar
  25. 25.
    Lionheart, W.R.B. and Coban, S.B., Nonlinear problems in fast tomography, Dev. X-Ray Tomogr. XI. Int. Soc. Opt. Photonics, 2017, vol. 10391, article 1039116.Google Scholar
  26. 26.
    Semerci, O. and Miller, E.L., A parametric level-set approach to simultaneous object identification and background reconstruction for dual-energy computed tomography, IEEE Trans Image Process., 2012, vol. 21, no. 5, pp. 2719–2734.CrossRefGoogle Scholar
  27. 27.
    Babaheidarian, P., Algorithms for enhanced artifact reduction and material recognition in computed tomography, Dissertation, Boston Univ., 2018.Google Scholar
  28. 28.
    Taschereau, R., Silverman, R.W., and Chatziioannou, A.F., Dual-energy attenuation coefficient decomposition with differential filtration and application to a microCT scanner, Phys. Med. Biol., vol. 55, no. 4, pp. 1141–1155. doi doi 10.1088/0031-9155/55/4/016Google Scholar
  29. 29.
  30. 30.
    Kramers, H.A. XCIII, On the theory of X-ray absorption and of the continuous X-ray spectrum, Philos. Mag., 1923, vol. 46, no. 275, pp. 836–871.CrossRefGoogle Scholar
  31. 31.
    Poludniowski, G.G., Calculation of x-ray spectra emerging from an x-ray tube. Part II. X-ray production and filtration in X-ray targets, Med. Phys., 2007, vol. 34, no. 6, pp. 2175–2186.CrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  • S. P. Osipov
    • 1
  • E. Yu. Usachev
    • 2
  • S. V. Chakhlov
    • 1
    Email author
  • S. A. Shchetinkin
    • 2
  • E. N. Kamysheva
    • 1
  1. 1.Tomsk Polytechnic UniversityTomskRussia
  2. 2.MIREA—Russian Technological UniversityMoscowRussia

Personalised recommendations