Experimental evaluation of effective atomic number of composite materials using back-scattering of gamma photons

2017 ◽  
Vol 172 (3-4) ◽  
pp. 204-215 ◽  
Author(s):  
Inderjeet Singh ◽  
Bhajan Singh ◽  
B. S. Sandhu ◽  
Arvind D. Sabharwal
Keyword(s):  
Composite Materials ◽  
Atomic Number ◽  
Experimental Evaluation ◽  
Effective Atomic Number ◽  
Back Scattering

BACK-SCATTERING AND SELF-ABSORPTION OF β−-PARTICLES

1963 ◽  
Vol 41 (9) ◽  
pp. 2283-2293 ◽  
Author(s):  
M. S. Lafleur ◽  
S. Kahana ◽  
T. F. Morris ◽  
L. Yaffe
Keyword(s):  
Atomic Number ◽  
Effective Atomic Number ◽  
The Self ◽  
Back Scattering

The self-absorption of the β−-radiation from S35 and P32 has been studied in various compounds. The function derived by Gora and Hickey has been shown to fit the data. The back-scattering of the β−-radiation from P32 by various elements and compounds has been examined and a semiempirical treatment used to suggest an effective atomic number for back-scattering by compounds.

Determination of effective atomic number of biomedical samples using Gamma ray back-scattering

2018 ◽  
Author(s):  
Inderjeet Singh ◽  
Bhajan Singh ◽  
B. S. Sandhu ◽  
Arvind D. Sabharwal
Keyword(s):  
Atomic Number ◽  
Gamma Ray ◽  
Effective Atomic Number ◽  
Back Scattering

Material Identification in Presence of Metal for Baggage Screening

2020 ◽  
Vol 2020 (14) ◽  
pp. 294-1-294-8
Author(s):  
Sandamali Devadithya ◽  
David Castañón
Keyword(s):  
Atomic Number ◽  
Effective Atomic Number ◽  
Simulated Data ◽  
Dual Energy ◽  
Basis Functions ◽  
Total Variation Regularization ◽  
Ct Scanner ◽  
Edge Preserving ◽  
Baggage Screening ◽  
Dual Energy Imaging

Dual-energy imaging has emerged as a superior way to recognize materials in X-ray computed tomography. To estimate material properties such as effective atomic number and density, one often generates images in terms of basis functions. This requires decomposition of the dual-energy sinograms into basis sinograms, and subsequently reconstructing the basis images. However, the presence of metal can distort the reconstructed images. In this paper we investigate how photoelectric and Compton basis functions, and synthesized monochromatic basis (SMB) functions behave in the presence of metal and its effect on estimation of effective atomic number and density. Our results indicate that SMB functions, along with edge-preserving total variation regularization, show promise for improved material estimation in the presence of metal. The results are demonstrated using both simulated data as well as data collected from a dualenergy medical CT scanner.

A Spectrum-Adaptive Decomposition Method for Effective Atomic Number Estimation Using Dual Energy CT

2020 ◽  
Vol 2020 (14) ◽  
pp. 293-1-293-7
Author(s):  
Ankit Manerikar ◽  
Fangda Li ◽  
Avinash C. Kak
Keyword(s):  
Atomic Number ◽  
Decomposition Method ◽  
Traditional Approach ◽  
Effective Atomic Number ◽  
Dual Energy ◽  
Performance Comparison ◽  
Estimation Methods ◽  
Dual Energy Ct ◽  
Projection Data ◽  
X Ray

Dual Energy Computed Tomography (DECT) is expected to become a significant tool for voxel-based detection of hazardous materials in airport baggage screening. The traditional approach to DECT imaging involves collecting the projection data using two different X-ray spectra and then decomposing the data thus collected into line integrals of two independent characterizations of the material properties. Typically, one of these characterizations involves the effective atomic number (Zeff) of the materials. However, with the X-ray spectral energies typically used for DECT imaging, the current best-practice approaches for dualenergy decomposition yield Zeff values whose accuracy range is limited to only a subset of the periodic-table elements, more specifically to (Z < 30). Although this estimation can be improved by using a system-independent ρe — Ze (SIRZ) space, the SIRZ transformation does not efficiently model the polychromatic nature of the X-ray spectra typically used in physical CT scanners. In this paper, we present a new decomposition method, AdaSIRZ, that corrects this shortcoming by adapting the SIRZ decomposition to the entire spectrum of an X-ray source. The method reformulates the X-ray attenuation equations as direct functions of (ρe, Ze) and solves for the coefficients using bounded nonlinear least-squares optimization. Performance comparison of AdaSIRZ with other Zeff estimation methods on different sets of real DECT images shows that AdaSIRZ provides a higher output accuracy for Zeff image reconstructions for a wider range of object materials.

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