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DOE OSTI · 2221818

Ultrasparse View X-ray Computed Tomography for 4D Imaging

Zheng, Yanjie·Hatzell, Kelsey B.
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Abstract

X-ray computed tomography (CT) is a noninvasive, nondestructive approach to imaging materials, material systems, and engineered components in two and three dimensions. Acquisition of three-dimensional (3D) images requires the collection of hundreds or thousands of through-thickness X-ray radiographic images from different angles. Such 3D data acquisition strategies commonly involve suboptimal temporal sampling for in situ and operando studies (4D imaging). Herein, we introduce a sparse-view imaging approach, Tomo-NeRF, which is capable of reconstructing high-fidelity 3D images from <10 twodimensional radiographic images. Experimental 2D and 3D X-ray images were used to test the reconstruction capability in two-view, four-view, and six-view scenarios. Tomo-NeRF is capable of reconstructing 3D images with a structural similarity of 0.9971–0.9975 and a voxel-wise accuracy of 81.83–89.59% from 2D experimentally obtained images. Furthermore, the reconstruction accuracy for the experimentally obtained images is less than the synthetic structures. Experimentally obtained images demonstrate a similarity of 0.9973–0.9984 and a voxelwise accuracy of 84.31–95.77%.

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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRYX-ray computed tomographyX-rayschemical structureimagingmaterialsneural radiance fieldoperando imagingphysical and chemical processessparse reconstructiontomographic reconstruction

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Zheng, Yanjie, Hatzell, Kelsey B.. 2023-07-12. Ultrasparse View X-ray Computed Tomography for 4D Imaging. https://doi.org/10.1021/acsami.3c06291

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