Model-based iterative reconstruction for neutron laminography

S. V. Venkatakrishnan; Ercan Cakmak; Hassina Billheux; Philip Bingham; Richard K. Archibald

doi:10.1109/ACSSC.2017.8335686

Model-based iterative reconstruction for neutron laminography

S. V. Venkatakrishnan, Ercan Cakmak, Hassina Billheux, Philip Bingham, Richard K. Archibald

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

Neutron-based parallel-beam laminography is an important 3D characterization tool because it can image thick specimens with unique shapes and provides a complimentary contrast to X-rays for several elements relevant to the material sciences and biology. However, the inversion of neutron laminography data is complicated because of the non-traditional geometry of the set-up, the presence of noise and the occurrence of gamma hits on the detector during the course of an experiment. In this paper, we present a model-based/regularized-inversion reconstruction algorithm for neutron laminography. We introduce a new forward-model/data fitting term and combine it with a flexible regularizer function to formulate the reconstruction as minimizing a cost-function. We then present a novel optimization algorithm that is based on combining a majorization-minimization technique with a first-order method that is amenable to simple parallelization on multi-core architectures. Using simulated and experimental data, we demonstrate that it is possible to acquire high quality reconstructions compared to the typically used filtered-back projection algorithm and algebraic reconstruction techniques.

Original language	English
Title of host publication	Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Editors	Michael B. Matthews
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1864-1869
Number of pages	6
ISBN (Electronic)	9781538618233
DOIs	https://doi.org/10.1109/ACSSC.2017.8335686
State	Published - Jul 2 2017
Event	51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 - Pacific Grove, United States Duration: Oct 29 2017 → Nov 1 2017

Publication series

Name	Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Volume	2017-October

Conference

Conference	51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Country/Territory	United States
City	Pacific Grove
Period	10/29/17 → 11/1/17

Funding

This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC05-00OR22725with the U.S. Department of Energy. The United States Government and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

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10.1109/ACSSC.2017.8335686

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Venkatakrishnan, S. V., Cakmak, E., Billheux, H., Bingham, P., & Archibald, R. K. (2017). Model-based iterative reconstruction for neutron laminography. In M. B. Matthews (Ed.), Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 (pp. 1864-1869). (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017; Vol. 2017-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACSSC.2017.8335686

Venkatakrishnan, S. V. ; Cakmak, Ercan ; Billheux, Hassina et al. / Model-based iterative reconstruction for neutron laminography. Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. editor / Michael B. Matthews. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1864-1869 (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017).

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abstract = "Neutron-based parallel-beam laminography is an important 3D characterization tool because it can image thick specimens with unique shapes and provides a complimentary contrast to X-rays for several elements relevant to the material sciences and biology. However, the inversion of neutron laminography data is complicated because of the non-traditional geometry of the set-up, the presence of noise and the occurrence of gamma hits on the detector during the course of an experiment. In this paper, we present a model-based/regularized-inversion reconstruction algorithm for neutron laminography. We introduce a new forward-model/data fitting term and combine it with a flexible regularizer function to formulate the reconstruction as minimizing a cost-function. We then present a novel optimization algorithm that is based on combining a majorization-minimization technique with a first-order method that is amenable to simple parallelization on multi-core architectures. Using simulated and experimental data, we demonstrate that it is possible to acquire high quality reconstructions compared to the typically used filtered-back projection algorithm and algebraic reconstruction techniques.",

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Venkatakrishnan, SV , Cakmak, E, Billheux, H, Bingham, P & Archibald, RK 2017, Model-based iterative reconstruction for neutron laminography. in MB Matthews (ed.), Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017, vol. 2017-October, Institute of Electrical and Electronics Engineers Inc., pp. 1864-1869, 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017, Pacific Grove, United States, 10/29/17. https://doi.org/10.1109/ACSSC.2017.8335686

Model-based iterative reconstruction for neutron laminography. / Venkatakrishnan, S. V.; Cakmak, Ercan; Billheux, Hassina et al.
Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. ed. / Michael B. Matthews. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1864-1869 (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017; Vol. 2017-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Venkatakrishnan, S. V.

AU - Cakmak, Ercan

AU - Billheux, Hassina

AU - Bingham, Philip

AU - Archibald, Richard K.

PY - 2017/7/2

Y1 - 2017/7/2

N2 - Neutron-based parallel-beam laminography is an important 3D characterization tool because it can image thick specimens with unique shapes and provides a complimentary contrast to X-rays for several elements relevant to the material sciences and biology. However, the inversion of neutron laminography data is complicated because of the non-traditional geometry of the set-up, the presence of noise and the occurrence of gamma hits on the detector during the course of an experiment. In this paper, we present a model-based/regularized-inversion reconstruction algorithm for neutron laminography. We introduce a new forward-model/data fitting term and combine it with a flexible regularizer function to formulate the reconstruction as minimizing a cost-function. We then present a novel optimization algorithm that is based on combining a majorization-minimization technique with a first-order method that is amenable to simple parallelization on multi-core architectures. Using simulated and experimental data, we demonstrate that it is possible to acquire high quality reconstructions compared to the typically used filtered-back projection algorithm and algebraic reconstruction techniques.

AB - Neutron-based parallel-beam laminography is an important 3D characterization tool because it can image thick specimens with unique shapes and provides a complimentary contrast to X-rays for several elements relevant to the material sciences and biology. However, the inversion of neutron laminography data is complicated because of the non-traditional geometry of the set-up, the presence of noise and the occurrence of gamma hits on the detector during the course of an experiment. In this paper, we present a model-based/regularized-inversion reconstruction algorithm for neutron laminography. We introduce a new forward-model/data fitting term and combine it with a flexible regularizer function to formulate the reconstruction as minimizing a cost-function. We then present a novel optimization algorithm that is based on combining a majorization-minimization technique with a first-order method that is amenable to simple parallelization on multi-core architectures. Using simulated and experimental data, we demonstrate that it is possible to acquire high quality reconstructions compared to the typically used filtered-back projection algorithm and algebraic reconstruction techniques.

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Venkatakrishnan SV , Cakmak E, Billheux H, Bingham P , Archibald RK. Model-based iterative reconstruction for neutron laminography. In Matthews MB, editor, Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1864-1869. (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017). doi: 10.1109/ACSSC.2017.8335686

Model-based iterative reconstruction for neutron laminography

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