Synthetic data generation for machine learning of 3D features using neutrons and X-rays

Pinghan Chu; Bradley Thomas Wolfe; David Paul Broughton; Robert Emil Reinovsky; Sky K. Sjue; Zhehui Wang

doi:10.1364/3D.2023.DM3A.4

Optica Imaging Congress (3D, COSI, DH, FLatOptics, IS, pcAOP)
Technical Digest Series (Optica Publishing Group, 2023),
paper DM3A.4
•https://doi.org/10.1364/3D.2023.DM3A.4

Synthetic data generation for machine learning of 3D features using neutrons and X-rays

Pinghan Chu, Bradley Thomas Wolfe, David Paul Broughton, Robert Emil Reinovsky, Sky K. Sjue, and Zhehui Wang

3D Image Acquisition and Display: Technology, Perception and Applications 2023

Boston, Massachusetts United States
14–17 August 2023
ISBN: 978-1-957171-28-9

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3D Sensing & Processing (DM3A)

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P. Chu, B. T. Wolfe, D. P. Broughton, R. E. Reinovsky, S. K. Sjue, and Z. Wang, "Synthetic data generation for machine learning of 3D features using neutrons and X-rays," in Optica Imaging Congress (3D, COSI, DH, FLatOptics, IS, pcAOP), Technical Digest Series (Optica Publishing Group, 2023), paper DM3A.4.

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Abstract

This study evaluates machine learning models TBNs, AttSets, and MVD on simulated X-ray and neutron scattering images, indicating the potential for more efficient and accurate 3D reconstruction in imaging.

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