Bayesian Abel inversion in quantitative X-ray radiography

Howard, Marylesa; Fowler, Michael; Luttman, Aaron; Mitchell, Stephen E.; Hock, Margaret C.

doi:10.1137/15M1018721

Title: Bayesian Abel inversion in quantitative X-ray radiography

Full Record
Other Related Research

Abstract

A common image formation process in high-energy X-ray radiography is to have a pulsed power source that emits X-rays through a scene, a scintillator that absorbs X-rays and uoresces in the visible spectrum in response to the absorbed photons, and a CCD camera that images the visible light emitted from the scintillator. The intensity image is related to areal density, and, for an object that is radially symmetric about a central axis, the Abel transform then gives the object's volumetric density. Two of the primary drawbacks to classical variational methods for Abel inversion are their sensitivity to the type and scale of regularization chosen and the lack of natural methods for quantifying the uncertainties associated with the reconstructions. In this work we cast the Abel inversion problem within a statistical framework in order to compute volumetric object densities from X-ray radiographs and to quantify uncertainties in the reconstruction. A hierarchical Bayesian model is developed with a likelihood based on a Gaussian noise model and with priors placed on the unknown density pro le, the data precision matrix, and two scale parameters. This allows the data to drive the localization of features in the reconstruction and results in a joint posteriormore »« less

Authors:

Howard, Marylesa ^[1]; Fowler, Michael ^[2]; Luttman, Aaron ^[1]; Mitchell, Stephen E. ^[1]; Hock, Margaret C. ^[3]

National Securities Technologies, LLC, Las Vegas, NV (United States)
Holliston, MA (United States)
Univ. of Alabama, Huntsville, AL (United States)

Publication Date:: 2016-05-19

Research Org.:: Nevada Test Site/National Security Technologies, LLC, Las Vegas, NV (United States); Nevada Test Site (NTS), Mercury, NV (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Security; USDOE National Nuclear Security Administration (NNSA), Office of Defense Programs (DP)

OSTI Identifier:: 1329259

Alternate Identifier(s):: OSTI ID: 1325541

Report Number(s):: DOE/NV/25946-2439
Journal ID: ISSN 1064-8275

Grant/Contract Number:: AC52-06NA25946

Resource Type:: Accepted Manuscript

Journal Name:: SIAM Journal on Scientific Computing

Additional Journal Information:: Journal Volume: 38; Journal Issue: 3; Journal ID: ISSN 1064-8275

Publisher:: SIAM

Country of Publication:: United States

Language:: English

Subject:: 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; X-ray radiography; inverse problems; Bayesian inference; Markov Chain Monte Carlo; maximum likelihood estimation; X-ray Radiography; Bayesian Inference

Citation Formats


                    Howard, Marylesa, Fowler, Michael, Luttman, Aaron, Mitchell, Stephen E., and Hock, Margaret C.. Bayesian Abel inversion in quantitative X-ray radiography.  United States: N. p., 2016. 
Web.  doi:10.1137/15M1018721.

Copy to clipboard


                    Howard, Marylesa, Fowler, Michael, Luttman, Aaron, Mitchell, Stephen E., & Hock, Margaret C.. Bayesian Abel inversion in quantitative X-ray radiography.  United States.  https://doi.org/10.1137/15M1018721

Copy to clipboard


                    Howard, Marylesa, Fowler, Michael, Luttman, Aaron, Mitchell, Stephen E., and Hock, Margaret C.. Thu .  
"Bayesian Abel inversion in quantitative X-ray radiography".  United States.  https://doi.org/10.1137/15M1018721.  https://www.osti.gov/servlets/purl/1329259.

Copy to clipboard


                    
@article{osti_1329259,

  title        = {Bayesian Abel inversion in quantitative X-ray radiography},

  author       = {Howard, Marylesa and Fowler, Michael and Luttman, Aaron and Mitchell, Stephen E. and Hock, Margaret C.},

  abstractNote = {A common image formation process in high-energy X-ray radiography is to have a pulsed power source that emits X-rays through a scene, a scintillator that absorbs X-rays and uoresces in the visible spectrum in response to the absorbed photons, and a CCD camera that images the visible light emitted from the scintillator. The intensity image is related to areal density, and, for an object that is radially symmetric about a central axis, the Abel transform then gives the object's volumetric density. Two of the primary drawbacks to classical variational methods for Abel inversion are their sensitivity to the type and scale of regularization chosen and the lack of natural methods for quantifying the uncertainties associated with the reconstructions. In this work we cast the Abel inversion problem within a statistical framework in order to compute volumetric object densities from X-ray radiographs and to quantify uncertainties in the reconstruction. A hierarchical Bayesian model is developed with a likelihood based on a Gaussian noise model and with priors placed on the unknown density pro le, the data precision matrix, and two scale parameters. This allows the data to drive the localization of features in the reconstruction and results in a joint posterior distribution for the unknown density pro le, the prior parameters, and the spatial structure of the precision matrix. Results of the density reconstructions and pointwise uncertainty estimates are presented for both synthetic signals and real data from a U.S. Department of Energy X-ray imaging facility.},

  doi          = {10.1137/15M1018721},

  journal      = {SIAM Journal on Scientific Computing},

  number       = 3,

  volume       = 38,

  place        = {United States},

  year         = {2016},

  month        = {5}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

https://doi.org/10.1137/15M1018721

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 14 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Generalized Uncertainty Quantification for Linear Inverse Problems in X-ray Imaging

Thesis/Dissertation Fowler, Michael James

In industrial and engineering applications, X-ray radiography has attained wide use as a data collection protocol for the assessment of material properties in cases where direct observation is not possible. The direct measurement of nuclear materials, particularly when they are under explosive or implosive loading, is not feasible, and radiography can serve as a useful tool for obtaining indirect measurements. In such experiments, high energy X-rays are pulsed through a scene containing material of interest, and a detector records a radiograph by measuring the radiation that is not attenuated in the scene. One approach to the analysis of these radiographsmore »« less
https://doi.org/10.2172/1179471

Full Text Available
Radiative properties of astrophysical matter : a quest to reproduce astrophysical conditions on earth.

Conference Bailey, James E

Experiments in terrestrial laboratories can be used to evaluate the physical models that interpret astronomical observations. The properties of matter in astrophysical objects are essential components of these models, but terrestrial laboratories struggle to reproduce the extreme conditions that often exist. Megajoule-class DOE/NNSA facilities such as the National Ignition Facility and Z can create unprecedented amounts of matter at extreme conditions, providing new capabilities to test astrophysical models with high accuracy. Experiments at these large facilities are challenging, and access is very competitive. However, the cylindrically-symmetric Z source emits radiation in all directions, enabling multiple physics experiments to be drivenmore »« less
Comparing implementations of penalized weighted least-squares sinogram restoration

Journal Article Forthmann, Peter ; Koehler, Thomas ; Defrise, Michel ; ... - Medical Physics

Purpose: A CT scanner measures the energy that is deposited in each channel of a detector array by x rays that have been partially absorbed on their way through the object. The measurement process is complex and quantitative measurements are always and inevitably associated with errors, so CT data must be preprocessed prior to reconstruction. In recent years, the authors have formulated CT sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. The authors have explored both penalizedmore »« less
https://doi.org/10.1118/1.3490476
Monte Carlo investigations of megavoltage cone-beam CT using thick, segmented scintillating detectors for soft tissue visualization

Journal Article Yi, Wang ; Antonuk, Larry E ; El-Mohri, Youcef ; ... - Medical Physics

Megavoltage cone-beam computed tomography (MV CBCT) is a highly promising technique for providing volumetric patient position information in the radiation treatment room. Such information has the potential to greatly assist in registering the patient to the planned treatment position, helping to ensure accurate delivery of the high energy therapy beam to the tumor volume while sparing the surrounding normal tissues. Presently, CBCT systems using conventional MV active matrix flat-panel imagers (AMFPIs), which are commonly used in portal imaging, require a relatively large amount of dose to create images that are clinically useful. This is due to the fact that themore »« less
https://doi.org/10.1118/1.2818957
WE-AB-BRB-00: Session in Memory of Robert J. Shalek: High Resolution Dosimetry from 2D to 3D to Real-Time 3D

Journal Article - Medical Physics

Despite widespread IMRT treatments at modern radiation therapy clinics, precise dosimetric commissioning of an IMRT system remains a challenge. In the most recent report from the Radiological Physics Center (RPC), nearly 20% of institutions failed an end-to-end test with an anthropomorphic head and neck phantom, a test that has rather lenient dose difference and distance-to-agreement criteria of 7% and 4 mm. The RPC report provides strong evidence that IMRT implementation is prone to error and that improved quality assurance tools are required. At the heart of radiation therapy dosimetry is the multidimensional dosimeter. However, due to the limited availability ofmore »« less
https://doi.org/10.1118/1.4957725

Similar Records