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Title: Tomographic Neutron Imaging using SIRT

Abstract

Neutron imaging is complementary to x-ray imaging in that materials such as water and plastic are highly attenuating while material such as metal is nearly transparent. We showcase tomographic imaging of a diesel particulate filter. Reconstruction is done using a modified version of SIRT called PSIRT. We expand on previous work and introduce Tikhonov regularization. We show that near-optimal relaxation can still be achieved. The algorithmic ideas apply to cone beam x-ray CT and other inverse problems.

Authors:
 [1];  [2];  [2]
  1. University of Tennessee, Knoxville (UTK)
  2. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Fuels, Engines and Emissions Research Center (FEERC)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1093159
DOE Contract Number:
DE-AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: The 12th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Lake Tahoe, CA, USA, 20130616, 20130621
Country of Publication:
United States
Language:
English

Citation Formats

Gregor, Jens, FINNEY, Charles E A, and Toops, Todd J. Tomographic Neutron Imaging using SIRT. United States: N. p., 2013. Web.
Gregor, Jens, FINNEY, Charles E A, & Toops, Todd J. Tomographic Neutron Imaging using SIRT. United States.
Gregor, Jens, FINNEY, Charles E A, and Toops, Todd J. 2013. "Tomographic Neutron Imaging using SIRT". United States. doi:.
@article{osti_1093159,
title = {Tomographic Neutron Imaging using SIRT},
author = {Gregor, Jens and FINNEY, Charles E A and Toops, Todd J},
abstractNote = {Neutron imaging is complementary to x-ray imaging in that materials such as water and plastic are highly attenuating while material such as metal is nearly transparent. We showcase tomographic imaging of a diesel particulate filter. Reconstruction is done using a modified version of SIRT called PSIRT. We expand on previous work and introduce Tikhonov regularization. We show that near-optimal relaxation can still be achieved. The algorithmic ideas apply to cone beam x-ray CT and other inverse problems.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2013,
month = 1
}

Conference:
Other availability
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