Retrieving Interface Evolution from Refraction-Enhanced X-ray Radiograph with a Deep Neural Network

S. Jiang; O. L. Landen; H. D. Whitley; S. Hamel; R. London; P. Sterne; D. S. Clark; S. B. Hansen; S. X. Hu; G.W. Collins; Y. Ping

doi:10.1364/DH.2021.DF2G.3

OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
OSA Technical Digest (Optica Publishing Group, 2021),
paper DF2G.3
•https://doi.org/10.1364/DH.2021.DF2G.3

Retrieving Interface Evolution from Refraction-Enhanced X-ray Radiograph with a Deep Neural Network

S. Jiang, O. L. Landen, H. D. Whitley, S. Hamel, R. London, P. Sterne, D. S. Clark, S. B. Hansen, S. X. Hu, G.W. Collins, and Y. Ping

Digital Holography and Three-Dimensional Imaging 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-89-7

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Tomography and Radiography Applications (DF2G)

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S. Jiang, O. L. Landen, H. D. Whitley, S. Hamel, R. London, P. Sterne, D. S. Clark, S. B. Hansen, S. X. Hu, G. W. Collins, and Y. Ping, "Retrieving Interface Evolution from Refraction-Enhanced X-ray Radiograph with a Deep Neural Network," in OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), H. Hua, B. Javidi, M. Martinez-Corral, O. Matoba, A. Stern, S. Thibault, T. Alieva, J. Ke, F. Willomitzer, F. Okten, P. Silveira, P. Banerjee, E. Stoykova, D. Chu, J. Park, F. Imai, C. Joo, M. Digman, D. Gardner, S. Gladysz, D. LeMaster, S. Basu, and O. Korotkova, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper DF2G.3.

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Abstract

We have used refraction-enhanced X-ray radiography to study the evolution of a heated CH/Be interface on OMEGA laser. The density profile as a function of time was retrieved with an untrained deep neural network, which can be used to infer thermal conductivity near the interface.

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