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

Glenn R. Myers; Shane J. Latham; Andrew M. Kingston; Jan Kolomazník; Václav Krajíček; Tomáš Krupka; Trond K. Varslot; Adrian P. Sheppard

doi:10.1117/12.2238258

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

Glenn R. Myers^*, Shane J. Latham, Andrew M. Kingston, Jan Kolomazník, Václav Krajíček, Tomáš Krupka, Trond K. Varslot, Adrian P. Sheppard

^*Corresponding author for this work

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

10 Citations (Scopus)

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 diffiult 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.

Original language	English
Title of host publication	Developments in X-Ray Tomography X
Editors	Ge Wang, Stuart R. Stock, Bert Muller
Publisher	SPIE
ISBN (Electronic)	9781510603257
DOIs	https://doi.org/10.1117/12.2238258
Publication status	Published - 2016
Event	Developments in X-Ray Tomography X - San Diego, United States Duration: 29 Aug 2016 → 31 Aug 2016

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	9967
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	Developments in X-Ray Tomography X
Country/Territory	United States
City	San Diego
Period	29/08/16 → 31/08/16

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10.1117/12.2238258

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Myers, G. R., Latham, S. J., Kingston, A. M., Kolomazník, J., Krajíček, V., Krupka, T., Varslot, T. K., & Sheppard, A. P. (2016). High cone-angle x-ray computed micro-tomography with 186 GigaVoxel datasets. In G. Wang, S. R. Stock, & B. Muller (Eds.), Developments in X-Ray Tomography X Article 99670U (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9967). SPIE. https://doi.org/10.1117/12.2238258

@inproceedings{c7af10bde60f4937aaa6b0e751ce56fd,

title = "High cone-angle x-ray computed micro-tomography with 186 GigaVoxel datasets",

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 diffiult 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.",

keywords = "Big data, GPGPU, Iterative tomographic reconstruction, MPI, Micro-tomography, Parallel computing, X-ray computed tomography",

author = "Myers, {Glenn R.} and Latham, {Shane J.} and Kingston, {Andrew M.} and Jan Kolomazn{\'i}k and V{\'a}clav Kraj{\'i}{\v c}ek and Tom{\'a}{\v s} Krupka and Varslot, {Trond K.} and Sheppard, {Adrian P.}",

year = "2016",

doi = "10.1117/12.2238258",

language = "English",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

editor = "Ge Wang and Stock, {Stuart R.} and Bert Muller",

booktitle = "Developments in X-Ray Tomography X",

address = "United States",

}

Myers, GR , Latham, SJ , Kingston, AM, Kolomazník, J, Krajíček, V, Krupka, T, Varslot, TK & Sheppard, AP 2016, High cone-angle x-ray computed micro-tomography with 186 GigaVoxel datasets. in G Wang, SR Stock & B Muller (eds), Developments in X-Ray Tomography X., 99670U, Proceedings of SPIE - The International Society for Optical Engineering, vol. 9967, SPIE, Developments in X-Ray Tomography X, San Diego, United States, 29/08/16. https://doi.org/10.1117/12.2238258

High cone-angle x-ray computed micro-tomography with 186 GigaVoxel datasets. / Myers, Glenn R.; Latham, Shane J.; Kingston, Andrew M. et al.
Developments in X-Ray Tomography X. ed. / Ge Wang; Stuart R. Stock; Bert Muller. SPIE, 2016. 99670U (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9967).

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

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AU - Myers, Glenn R.

AU - Latham, Shane J.

AU - Kingston, Andrew M.

AU - Kolomazník, Jan

AU - Krajíček, Václav

AU - Krupka, Tomáš

AU - Varslot, Trond K.

AU - Sheppard, Adrian P.

PY - 2016

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N2 - 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 diffiult 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.

AB - 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 diffiult 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.

KW - Big data

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KW - Iterative tomographic reconstruction

KW - MPI

KW - Micro-tomography

KW - Parallel computing

KW - X-ray computed tomography

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T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Developments in X-Ray Tomography X

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A2 - Stock, Stuart R.

A2 - Muller, Bert

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T2 - Developments in X-Ray Tomography X

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ER -

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

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