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Title: Robust statistical reconstruction for charged particle tomography

Abstract

Systems and methods for charged particle detection including statistical reconstruction of object volume scattering density profiles from charged particle tomographic data to determine the probability distribution of charged particle scattering using a statistical multiple scattering model and determine a substantially maximum likelihood estimate of object volume scattering density using expectation maximization (ML/EM) algorithm to reconstruct the object volume scattering density. The presence of and/or type of object occupying the volume of interest can be identified from the reconstructed volume scattering density profile. The charged particle tomographic data can be cosmic ray muon tomographic data from a muon tracker for scanning packages, containers, vehicles or cargo. The method can be implemented using a computer program which is executable on a computer.

Inventors:
; ; ; ; ; ; ;
Publication Date:
Research Org.:
LANL (Los Alamos National Laboratory (LANL), Los Alamos, NM (United States))
Sponsoring Org.:
USDOE
OSTI Identifier:
1097256
Patent Number(s):
8,552,370
Application Number:
11/977,409
Assignee:
Los Alamos National Security, LLC (Los Alamos, NM)
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Citation Formats

Schultz, Larry Joe, Klimenko, Alexei Vasilievich, Fraser, Andrew Mcleod, Morris, Christopher, Orum, John Christopher, Borozdin, Konstantin N, Sossong, Michael James, and Hengartner, Nicolas W. Robust statistical reconstruction for charged particle tomography. United States: N. p., 2013. Web.
Schultz, Larry Joe, Klimenko, Alexei Vasilievich, Fraser, Andrew Mcleod, Morris, Christopher, Orum, John Christopher, Borozdin, Konstantin N, Sossong, Michael James, & Hengartner, Nicolas W. Robust statistical reconstruction for charged particle tomography. United States.
Schultz, Larry Joe, Klimenko, Alexei Vasilievich, Fraser, Andrew Mcleod, Morris, Christopher, Orum, John Christopher, Borozdin, Konstantin N, Sossong, Michael James, and Hengartner, Nicolas W. Tue . "Robust statistical reconstruction for charged particle tomography". United States. https://www.osti.gov/servlets/purl/1097256.
@article{osti_1097256,
title = {Robust statistical reconstruction for charged particle tomography},
author = {Schultz, Larry Joe and Klimenko, Alexei Vasilievich and Fraser, Andrew Mcleod and Morris, Christopher and Orum, John Christopher and Borozdin, Konstantin N and Sossong, Michael James and Hengartner, Nicolas W},
abstractNote = {Systems and methods for charged particle detection including statistical reconstruction of object volume scattering density profiles from charged particle tomographic data to determine the probability distribution of charged particle scattering using a statistical multiple scattering model and determine a substantially maximum likelihood estimate of object volume scattering density using expectation maximization (ML/EM) algorithm to reconstruct the object volume scattering density. The presence of and/or type of object occupying the volume of interest can be identified from the reconstructed volume scattering density profile. The charged particle tomographic data can be cosmic ray muon tomographic data from a muon tracker for scanning packages, containers, vehicles or cargo. The method can be implemented using a computer program which is executable on a computer.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2013},
month = {10}
}

Patent:

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