Abstract:

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.

Keywords: X-ray Micro Computed tomography, Data Analysis, Mineral Characterization, Texture, mineralogy.

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