High cone-angle x-ray computed micro-tomography with 186 GigaVoxel datasets

Authors

Myers, Glenn
Latham, Shane
Kingston, Andrew
Kolomazník, Jan
Krajíček, Václav
Krupka, Tomáš
Varslot, Trond K.
Sheppard, Adrian

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Society of Photo-Optical Instrumentation Engineers (SPIE)

Abstract

X-ray computed micro-tomography systems are able to collect data with sub-micron resolution. This high- resolution imaging has many applications but is particularly important in the study of porous materials, where the sub-micron structure can dictate large-scale physical properties (e.g. carbonates, shales, or human bone). Sample preparation and mounting become difficult for these materials below 2mm diameter: consequently, a typical ultra-micro-CT reconstruction volume (with sub-micron resolution) will be around 3k × 3k × 10k voxels, with some reconstructions becoming much larger. In this paper, we discuss the hardware (MPI-parallel CPU/GPU) and software (python/C++/CUDA) tools used at the ANU CTlab to reconstruct ∼186 GigaVoxel datasets.

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Citation

Glenn R. Myers, Shane J. Latham, Andrew M. Kingston, Jan Kolomazník, Václav Krajíček, Tomáš Krupka, Trond K. Varslot, Adrian P. Sheppard, "High cone-angle x-ray computed micro-tomography with 186 GigaVoxel datasets," Proc. SPIE 9967, Developments in X-Ray Tomography X, 99670U (4 October 2016); doi: 10.1117/12.2238258

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Proceedings of SPIE

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Open Access

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