X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis Methods
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...
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doaj-c735d1caedfa4e37b63e4b8b59d785b32020-11-25T02:17:13ZengMDPI AGMinerals2075-163X2019-03-019318310.3390/min9030183min9030183X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis MethodsPratama Istiadi Guntoro0Yousef Ghorbani1Pierre-Henri Koch2Jan Rosenkranz3MiMeR—Minerals and Metallurgical Engineering, Luleå University of Technology, SE-971 87 Luleå, SwedenMiMeR—Minerals and Metallurgical Engineering, Luleå University of Technology, SE-971 87 Luleå, SwedenMiMeR—Minerals and Metallurgical Engineering, Luleå University of Technology, SE-971 87 Luleå, SwedenMiMeR—Minerals and Metallurgical Engineering, Luleå University of Technology, SE-971 87 Luleå, SwedenThe 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.http://www.mdpi.com/2075-163X/9/3/183X-ray microcomputed tomographydata analysismineral characterizationtexturemineralogy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pratama Istiadi Guntoro Yousef Ghorbani Pierre-Henri Koch Jan Rosenkranz |
spellingShingle |
Pratama Istiadi Guntoro Yousef Ghorbani Pierre-Henri Koch Jan Rosenkranz X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis Methods Minerals X-ray microcomputed tomography data analysis mineral characterization texture mineralogy |
author_facet |
Pratama Istiadi Guntoro Yousef Ghorbani Pierre-Henri Koch Jan Rosenkranz |
author_sort |
Pratama Istiadi Guntoro |
title |
X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis Methods |
title_short |
X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis Methods |
title_full |
X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis Methods |
title_fullStr |
X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis Methods |
title_full_unstemmed |
X-ray Microcomputed Tomography (µCT) for Mineral Characterization: A Review of Data Analysis Methods |
title_sort |
x-ray microcomputed tomography (µct) for mineral characterization: a review of data analysis methods |
publisher |
MDPI AG |
series |
Minerals |
issn |
2075-163X |
publishDate |
2019-03-01 |
description |
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. |
topic |
X-ray microcomputed tomography data analysis mineral characterization texture mineralogy |
url |
http://www.mdpi.com/2075-163X/9/3/183 |
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