Journal of Nuclear Science, Engineering and Technology (JONSAT)
In cooperation with the Iranian Nuclear Society

Contrast evaluation of digital industrial radiography images using FLUKA simulation

Document Type : Research Paper

Authors

M. Khodakarami 1
B. Rokrok 2
M. Salehi Barough 1

1 Department of Nuclear Engineering, Central Tehran Branch, Islamic Azad University, P.O.Box: 13185-768, Tehran-Iran

2 Reactor and Nuclear Safety Research School, Nuclear Science and Technology Research Institute, AEOI, P.O.Box: 14155-1339, Tehran – Iran

https://doi.org/10.24200/nst.2020.1101
Abstract
Monte Carlo method is widely used for simulation of industrial and medical radiography due to its powerful ability to simulate statistical phenomena such as radiation generation and transport, and detection processes. Digital radiography is practically applied in two branches of computational radiography (CR) and direct radiography (DR). In this study, computational radiography simulation using the FLUKA Monte Carlo code was developed to provide a framework for studying image contrast as one of the most important parameters of image quality. To investigate the contrast a standard aluminum sensitivity component made of ASTM 1647 standard was used. The simulation of this gauge, along with a complete simulation of the X-ray generator and imaging plate, has been done to assess the image contrast, and and a method has been presented to examine the image contrast. In order to validate the proposed method, practical experiments have been carried out on the contrast sensitivity standard gauge. The simulation results obtained through the proposed method are in good agreement with the results of practical experiments.

Highlights

1.             ASME Section V, Article 2, Radiographic Examination, (American Society of Mechanical Engineers, 2019).

 

2.             R. Talei, M. Shahriari, S.M. Aghamiri, Qualitative study of FLUKA software in simulation and design of X-ray rays obtained from X-ray tube, Iranian Journal of Medical Physics, 3(12) (2006) (In Persian).

 

3.             M. Saghafi, N. Vosoughi, Simulation of X-ray Imaging of Industrial Parts using the Monte Carlo Method, 4th Conference on Machine Tracking and Troubleshooting, Sharif University of Technology, Tehran, Iran (2009) (In Persian).

 

4.             M. Abdollahzadeh, H. Nemati, Determination of the dose of portable X-ray generator using the MCNP simulation code and its comparison with experimental values, First International Conference of Physics and Mathematics (2015) (In Persian).

 

5.             S.C.A. Correa, et al, Computed radiography simulation using the Monte Carlo code MCNPX, Applied Radiation and Isotopes, 68 (9), 1662 (2010).

 

6.             E. Nazemi, et al, Simulation of  A Complete X-ray digital radiographic system for Industrial Application, Applied Radiation and Isotopes, 139, 294 (2018).

 

7.             IPEM Report No. 78, Catalogue of Diagnostic X-ray Spectra and other data, Institute of Physics and Engineering in Medicine (1997).

 

8.             N. Metropolis, S. Ulam, The Monte Carlo Method, Journal of the American Statistical Association, 44(247), 335-341 (1949).

 

9.             N. Metropolis, The beginning of the Monte Carlo method, Los Alamos Science, 125-130 (1987).

 

10.          Wikipedia, Monte Carlo Method (2018).

 

11.          Official FLUKA Site, FLUKA Manual, www.fluka.org (2018).

 

12.          Balteau NDT, BALTOSPOT-CERAM 235, www.balteau.com (2018).

 

13.          ISO 19232-1, Non-destructive testing -- Image quality of radiographs -- Part 1: Determination of the image quality value using wire-type image quality indicators, (International Standard Organization, 2013).

 

14.          ISO 19232-2, Non-destructive testing -- Image quality of radiographs -- Part 2: Determination of the image quality value using step/hole-type image quality indicators, (International Standard Organization, 2013).

 

15.          ASTM E1025, Standard Practice for Design, Manufacture, and Material Grouping Classification of Hole-Type Image Quality Indicators (IQI) Used for Radiography, (American Society for Testing Materials, 2018).

 

16.          ISO 19232-5, Non-destructive testing -- Image quality of radiographs -- Part 5: Determination of the image unsharpness and basic spatial resolution value using duplex wire-type image quality indicators, (International Standard Organization, 2018).

 

17.          ASTM E1647, Standard Practice for Determining Contrast Sensitivity in Radiology, (American Society for Testing Materials, 2016).

 

18.          Bushberg, et al, The Essential Physics of Medical Imaging, (Lippincott Williams, 2002).

 

19.          AAPM REPORT NO. 93, Acceptance Testing and Quality Control of Photostimulable Storage Phosphor Imaging Systems, (Report of AAPM Task Group 10, October 2006).

Keywords

Digital radiography
Contrast
Imaging plate
Contrast sensitivity
FLUKA code
1.             ASME Section V, Article 2, Radiographic Examination, (American Society of Mechanical Engineers, 2019).
 
2.             R. Talei, M. Shahriari, S.M. Aghamiri, Qualitative study of FLUKA software in simulation and design of X-ray rays obtained from X-ray tube, Iranian Journal of Medical Physics, 3(12) (2006) (In Persian).
 
3.             M. Saghafi, N. Vosoughi, Simulation of X-ray Imaging of Industrial Parts using the Monte Carlo Method, 4th Conference on Machine Tracking and Troubleshooting, Sharif University of Technology, Tehran, Iran (2009) (In Persian).
 
4.             M. Abdollahzadeh, H. Nemati, Determination of the dose of portable X-ray generator using the MCNP simulation code and its comparison with experimental values, First International Conference of Physics and Mathematics (2015) (In Persian).
 
5.             S.C.A. Correa, et al, Computed radiography simulation using the Monte Carlo code MCNPX, Applied Radiation and Isotopes, 68 (9), 1662 (2010).
 
6.             E. Nazemi, et al, Simulation of  A Complete X-ray digital radiographic system for Industrial Application, Applied Radiation and Isotopes, 139, 294 (2018).
 
7.             IPEM Report No. 78, Catalogue of Diagnostic X-ray Spectra and other data, Institute of Physics and Engineering in Medicine (1997).
 
8.             N. Metropolis, S. Ulam, The Monte Carlo Method, Journal of the American Statistical Association, 44(247), 335-341 (1949).
 
9.             N. Metropolis, The beginning of the Monte Carlo method, Los Alamos Science, 125-130 (1987).
 
10.          Wikipedia, Monte Carlo Method (2018).
 
11.          Official FLUKA Site, FLUKA Manual, www.fluka.org (2018).
 
12.          Balteau NDT, BALTOSPOT-CERAM 235, www.balteau.com (2018).
 
13.          ISO 19232-1, Non-destructive testing -- Image quality of radiographs -- Part 1: Determination of the image quality value using wire-type image quality indicators, (International Standard Organization, 2013).
 
14.          ISO 19232-2, Non-destructive testing -- Image quality of radiographs -- Part 2: Determination of the image quality value using step/hole-type image quality indicators, (International Standard Organization, 2013).
 
15.          ASTM E1025, Standard Practice for Design, Manufacture, and Material Grouping Classification of Hole-Type Image Quality Indicators (IQI) Used for Radiography, (American Society for Testing Materials, 2018).
 
16.          ISO 19232-5, Non-destructive testing -- Image quality of radiographs -- Part 5: Determination of the image unsharpness and basic spatial resolution value using duplex wire-type image quality indicators, (International Standard Organization, 2018).
 
17.          ASTM E1647, Standard Practice for Determining Contrast Sensitivity in Radiology, (American Society for Testing Materials, 2016).
 
18.          Bushberg, et al, The Essential Physics of Medical Imaging, (Lippincott Williams, 2002).
 
19.          AAPM REPORT NO. 93, Acceptance Testing and Quality Control of Photostimulable Storage Phosphor Imaging Systems, (Report of AAPM Task Group 10, October 2006).

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