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Title: Detecting and quantifying materials in containers utilizing an inverse algorithm with adaptive regularization

Abstract

A method, system and computer program product for automatically detecting and quantifying materials in containers (e.g., luggage, storage containers, equipment or componentry for processing or handling). An X-ray radiograph of a container is generated. A set of materials of interest (e.g., plutonium, steel) is selected to determine if the object comprises or contains materials of interest. An estimate of the areal densities or thicknesses of each of the selected materials of interest is obtained by minimizing an objective function with respect to the areal densities or thicknesses for each of the selected materials of interest. Adaptive regularization is implemented in the objective function to improve optimization results by adding a constraint to the objective function, where the constraint penalizes the objective function for solutions that do not line up with a prior belief about the solution form (e.g., the solution should not be negative or especially noisy).

Inventors:
; ; ; ; ;
Issue Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1483286
Patent Number(s):
10078150
Application Number:
15/093,525
Assignee:
Board of Regents, The University of Texas System (Austin, TX)
Patent Classifications (CPCs):
G - PHYSICS G01 - MEASURING G01N - INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
G - PHYSICS G01 - MEASURING G01V - GEOPHYSICS
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Patent
Resource Relation:
Patent File Date: 2016 Apr 07
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Deinert, Mark, Gilbert, Andrew J., McDonald, Benjamin S., Robinson, Sean M., Jarman, Ken D., and White, Tim A. Detecting and quantifying materials in containers utilizing an inverse algorithm with adaptive regularization. United States: N. p., 2018. Web.
Deinert, Mark, Gilbert, Andrew J., McDonald, Benjamin S., Robinson, Sean M., Jarman, Ken D., & White, Tim A. Detecting and quantifying materials in containers utilizing an inverse algorithm with adaptive regularization. United States.
Deinert, Mark, Gilbert, Andrew J., McDonald, Benjamin S., Robinson, Sean M., Jarman, Ken D., and White, Tim A. Tue . "Detecting and quantifying materials in containers utilizing an inverse algorithm with adaptive regularization". United States. https://www.osti.gov/servlets/purl/1483286.
@article{osti_1483286,
title = {Detecting and quantifying materials in containers utilizing an inverse algorithm with adaptive regularization},
author = {Deinert, Mark and Gilbert, Andrew J. and McDonald, Benjamin S. and Robinson, Sean M. and Jarman, Ken D. and White, Tim A.},
abstractNote = {A method, system and computer program product for automatically detecting and quantifying materials in containers (e.g., luggage, storage containers, equipment or componentry for processing or handling). An X-ray radiograph of a container is generated. A set of materials of interest (e.g., plutonium, steel) is selected to determine if the object comprises or contains materials of interest. An estimate of the areal densities or thicknesses of each of the selected materials of interest is obtained by minimizing an objective function with respect to the areal densities or thicknesses for each of the selected materials of interest. Adaptive regularization is implemented in the objective function to improve optimization results by adding a constraint to the objective function, where the constraint penalizes the objective function for solutions that do not line up with a prior belief about the solution form (e.g., the solution should not be negative or especially noisy).},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {9}
}

Patent:

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