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Title: Quantitative tomography simulations and reconstruction algorithms

Abstract

X-ray, neutron and proton transmission radiography and computed tomography (CT) are important diagnostic tools that are at the heart of LLNLs effort to meet the goals of the DOE's Advanced Radiography Campaign. This campaign seeks to improve radiographic simulation and analysis so that radiography can be a useful quantitative diagnostic tool for stockpile stewardship. Current radiographic accuracy does not allow satisfactory separation of experimental effects from the true features of an object's tomographically reconstructed image. This can lead to difficult and sometimes incorrect interpretation of the results. By improving our ability to simulate the whole radiographic and CT system, it will be possible to examine the contribution of system components to various experimental effects, with the goal of removing or reducing them. In this project, we are merging this simulation capability with a maximum-likelihood (constrained-conjugate-gradient-CCG) reconstruction technique yielding a physics-based, forward-model image-reconstruction code. In addition, we seek to improve the accuracy of computed tomography from transmission radiographs by studying what physics is needed in the forward model. During FY 2000, an improved version of the LLNL ray-tracing code called HADES has been coupled with a recently developed LLNL CT algorithm known as CCG. The problem of image reconstruction is expressedmore » as a large matrix equation relating a model for the object being reconstructed to its projections (radiographs). Using a constrained-conjugate-gradient search algorithm, a maximum likelihood solution is sought. This search continues until the difference between the input measured radiographs or projections and the simulated or calculated projections is satisfactorily small. We developed a 2D HADES-CCG CT code that uses full ray-tracing simulations from HADES as the projector. Often an object has axial symmetry and it is desirable to reconstruct into a 2D r-z mesh with a limited number of projections. The physics (e.g., scattering and detector response) required in the HADES code is determined from Monte Carlo simulations. The current version of HADES-CCG reconstructs into a volume-density mesh made of one material and assumes a monochromatic source.« less

Authors:
; ; ; ; ; ; ;
Publication Date:
Research Org.:
Lawrence Livermore National Lab., CA (US)
Sponsoring Org.:
US Department of Energy (US)
OSTI Identifier:
15005122
Report Number(s):
UCRL-ID-141591
TRN: US0401558
DOE Contract Number:  
W-7405-ENG-48
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 1 Nov 2000
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; 42 ENGINEERING; ACCURACY; ALGORITHMS; AXIAL SYMMETRY; COMPUTERIZED TOMOGRAPHY; IMAGES; LAWRENCE LIVERMORE NATIONAL LABORATORY; NEUTRONS; PHYSICS; PROTONS; SCATTERING; SIMULATION; STOCKPILES; TOMOGRAPHY

Citation Formats

Martz, H E, Aufderheide, M B, Goodman, D, Schach von Wittenau, A, Logan, C, Hall, J, Jackson, J, and Slone, D. Quantitative tomography simulations and reconstruction algorithms. United States: N. p., 2000. Web. doi:10.2172/15005122.
Martz, H E, Aufderheide, M B, Goodman, D, Schach von Wittenau, A, Logan, C, Hall, J, Jackson, J, & Slone, D. Quantitative tomography simulations and reconstruction algorithms. United States. doi:10.2172/15005122.
Martz, H E, Aufderheide, M B, Goodman, D, Schach von Wittenau, A, Logan, C, Hall, J, Jackson, J, and Slone, D. Wed . "Quantitative tomography simulations and reconstruction algorithms". United States. doi:10.2172/15005122. https://www.osti.gov/servlets/purl/15005122.
@article{osti_15005122,
title = {Quantitative tomography simulations and reconstruction algorithms},
author = {Martz, H E and Aufderheide, M B and Goodman, D and Schach von Wittenau, A and Logan, C and Hall, J and Jackson, J and Slone, D},
abstractNote = {X-ray, neutron and proton transmission radiography and computed tomography (CT) are important diagnostic tools that are at the heart of LLNLs effort to meet the goals of the DOE's Advanced Radiography Campaign. This campaign seeks to improve radiographic simulation and analysis so that radiography can be a useful quantitative diagnostic tool for stockpile stewardship. Current radiographic accuracy does not allow satisfactory separation of experimental effects from the true features of an object's tomographically reconstructed image. This can lead to difficult and sometimes incorrect interpretation of the results. By improving our ability to simulate the whole radiographic and CT system, it will be possible to examine the contribution of system components to various experimental effects, with the goal of removing or reducing them. In this project, we are merging this simulation capability with a maximum-likelihood (constrained-conjugate-gradient-CCG) reconstruction technique yielding a physics-based, forward-model image-reconstruction code. In addition, we seek to improve the accuracy of computed tomography from transmission radiographs by studying what physics is needed in the forward model. During FY 2000, an improved version of the LLNL ray-tracing code called HADES has been coupled with a recently developed LLNL CT algorithm known as CCG. The problem of image reconstruction is expressed as a large matrix equation relating a model for the object being reconstructed to its projections (radiographs). Using a constrained-conjugate-gradient search algorithm, a maximum likelihood solution is sought. This search continues until the difference between the input measured radiographs or projections and the simulated or calculated projections is satisfactorily small. We developed a 2D HADES-CCG CT code that uses full ray-tracing simulations from HADES as the projector. Often an object has axial symmetry and it is desirable to reconstruct into a 2D r-z mesh with a limited number of projections. The physics (e.g., scattering and detector response) required in the HADES code is determined from Monte Carlo simulations. The current version of HADES-CCG reconstructs into a volume-density mesh made of one material and assumes a monochromatic source.},
doi = {10.2172/15005122},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Nov 01 00:00:00 EST 2000},
month = {Wed Nov 01 00:00:00 EST 2000}
}

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