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A novel method for non-destructive Compton scatter imaging based on the genetic algorithm

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Central European Journal of Physics

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Abstract

Compton scattering tomography is widely used in numerous applications such as biomedical imaging, nondestructive industrial testing and environmental survey, etc. This paper proposes the use of the genetic algorithm (GA), which utilizes bio-inspired mathematical models, to construct an image of the insides of a test object via the scattered photons, from a voxel within the object. A NaI(Tl) scintillation detector and a 185 MBq 137Cs gamma ray source were used in the experimental measurements. The obtained results show that the proposed GA based method performs well in constructing images of objects.

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References

  1. A. D. Sabharwal, B. S. Sandhu, B. Singh, Radiat. Meas., 44, 411 (2009)

    Article  Google Scholar 

  2. J. Wang, Y. Wang, Z. Chi, IEE Proc.-Sci. Meas. Technol., 146, 235 (1999)

    Article  Google Scholar 

  3. G. F. Knoll, Radiation Detection and Measurement, 4th edition, (John Wiley & Sons, 2010)

    Google Scholar 

  4. G. N. Ramachandran, A. V. Lakshminarayanan, Proc. Nat. Acad., Sci. 68, 2236 (1971)

    Article  MathSciNet  ADS  Google Scholar 

  5. H. Barrett, L. Parra, T. White, J. Optical Soc. Amer. A 14, 2914 (1997)

    Article  ADS  Google Scholar 

  6. L. Parra, H. H. Barrett, J. Nucl.Med., 37, 486 (1996)

    Google Scholar 

  7. T. Tomitani, M. Hirasawa, Phys. Med. Biol., 47, 2129 (2002)

    Article  Google Scholar 

  8. S. M. Kim, J. S. Lee, S. J. Lee, IEEE Nucl. Sci. Symp. Conf. Rec., 4, 3070 (2007)

    Google Scholar 

  9. J. Wang, O. M. Omidvar(Ed.), Progress in Neural Networks. (Ablex, Stamford 1994) 319

    Google Scholar 

  10. P. Borne, D. Popescu, F. Gh. Filip, D. Stefanoiu, Optimization in Engineering Sciences, 11th edition (Wiley-ISTE, Croydon 2012)

    Google Scholar 

  11. S. G. Prussin, Nuclear Physics for Application, (WILEY-VCHVerlag GmbH & Co. 2007)

    Google Scholar 

  12. R. D. Evans, The Atomic nucleus, (McGraw-Hill, New-York, 1955)

    MATH  Google Scholar 

  13. E. M. A. Hussein, Computed Radiation Imaging Physics and Mathematics of Forward and Inverse Problems, (Elsevier, Waltham 2011)

    Google Scholar 

  14. J. Nocedal, Numerical Optimization, ( Springer-Verlag, New York 1999)

    Book  MATH  Google Scholar 

  15. D.E. Goldberg, Genetic Algorithms in Search Optimization and Machine Learning, (Addison-Wesley, Reading, MA, 1989)

    MATH  Google Scholar 

  16. R. L. Haupt, S. E. Haupt, Practical Genetic Algorithms, 2edition (John Wiley and Sons, Hoboken 2004)

    MATH  Google Scholar 

  17. S. N. Sivanandam, S. N. Deepa, Introduction to Genetic Algorithms (Springer-Verlag, Berlin Heidelberg 2008)

    MATH  Google Scholar 

  18. F. Rothlauf, Representations for Genetic and Evolutionary Algorithms, (Springer-Verlag, Berlin Heidelberg 2006)

    Google Scholar 

  19. H. Aytug, G. J. Koehler, ORSA J. Comput., 8, 183 (1996)

    Article  MATH  Google Scholar 

  20. C. Cheng, Z. Xu, C. Sui, Opt. Commun., 227, 371 (2003)

    Article  ADS  Google Scholar 

  21. A. B. Djurisic, Opt. Commun., 151, 147 (1998)

    Article  ADS  Google Scholar 

  22. M.B. Saddi, B.S. Sandhu, B. Singh, Ann. Nuc. Energy, 33, 271 (2006)

    Article  Google Scholar 

  23. G. T. Herman, Image reconstruction for projections, (Demic Press, New York, 1980)

    Google Scholar 

  24. P. Campisi, K. O. Egiazarian, Blind Image Deconvolution: Theory and Applications, (CRC PressINC, 2007)

    Book  Google Scholar 

Download references

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Authors and Affiliations

  1. Physics Faculty, University of Tabriz, P.O.Box 51666-16471, Tabriz, Iran

    Saleh Ashrafi, Okhtay Jahanbakhsh, Davood Alizadeh & Behrooz Salehpour

Authors
  1. Saleh Ashrafi
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  2. Okhtay Jahanbakhsh
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  3. Davood Alizadeh
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  4. Behrooz Salehpour
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Corresponding author

Correspondence to Saleh Ashrafi.

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Ashrafi, S., Jahanbakhsh, O., Alizadeh, D. et al. A novel method for non-destructive Compton scatter imaging based on the genetic algorithm. centr.eur.j.phys. 11, 560–567 (2013). https://doi.org/10.2478/s11534-013-0239-8

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  • DOI: https://doi.org/10.2478/s11534-013-0239-8

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