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X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis Methods
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering.ORCID iD: 0000-0002-8693-1054
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering.ORCID iD: 0000-0002-5228-3888
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering.ORCID iD: 0000-0003-4800-9533
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering.
2019 (English)In: Minerals, ISSN 2075-163X, E-ISSN 2075-163X, Vol. 9, no 3, article id 183Article in journal (Refereed) Published
Abstract [en]

The main advantage of X-ray microcomputed tomography (µCT) as a non-destructive imaging tool lies in its ability to analyze the three-dimensional (3D) interior of a sample, therefore eliminating the stereological error exhibited in conventional two-dimensional (2D) image analysis. Coupled with the correct data analysis methods, µCT allows extraction of textural and mineralogical information from ore samples. This study provides a comprehensive overview on the available and potentially useful data analysis methods for processing 3D datasets acquired with laboratory µCT systems. Our study indicates that there is a rapid development of new techniques and algorithms capable of processing µCT datasets, but application of such techniques is often sample-specific. Several methods that have been successfully implemented for other similar materials (soils, aggregates, rocks) were also found to have the potential to be applied in mineral characterization. The main challenge in establishing a µCT system as a mineral characterization tool lies in the computational expenses of processing the large 3D dataset. Additionally, since most of the µCT dataset is based on the attenuation of the minerals, the presence of minerals with similar attenuations limits the capability of µCT in mineral segmentation. Further development on the data processing workflow is needed to accelerate the breakthrough of µCT as an analytical tool in mineral characterization.

Place, publisher, year, edition, pages
Basel, Switzerland: MDPI, 2019. Vol. 9, no 3, article id 183
Keywords [en]
X-ray microcomputed tomography, data analysis, mineral characterization, texture, mineralogy
National Category
Metallurgy and Metallic Materials
Research subject
Mineral Processing
Identifiers
URN: urn:nbn:se:ltu:diva-73224DOI: 10.3390/min9030183ISI: 000464421700002Scopus ID: 2-s2.0-85064225739OAI: oai:DiVA.org:ltu-73224DiVA, id: diva2:1296775
Note

Validerad;2019;Nivå 2;2019-03-18 (svasva)

Available from: 2019-03-18 Created: 2019-03-18 Last updated: 2019-04-30Bibliographically approved

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Guntoro, Pratama IstiadiGhorbani, YousefKoch, Pierre-HenriRosenkranz, Jan

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