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Projecting into the Third Dimension: 3D Ore Mineralogy via Machine Learning of Automated Mineralogy and X-Ray Microscopy

Published online by Cambridge University Press:  05 August 2019

Matthew R. Ball ,
Joshua F. Einsle ,
Matthew Andrew ,
David D. McNamara ,
Richard J.M. Taylor  and
Richard J. Harrison
Matthew R. Ball*
Affiliation:
Department of Earth Sciences, University of Cambridge, Cambridge, UK.
Joshua F. Einsle
Affiliation:
Department of Earth Science and Engineering, Imperial College, London, UK.
Matthew Andrew
Affiliation:
Carl Zeiss X-ray Microscopy, Pleasanton, CA, USA.
David D. McNamara
Affiliation:
Earth and Ocean Sciences, National University of Ireland, Galway, Ireland.
Richard J.M. Taylor
Affiliation:
Department of Earth Sciences, University of Cambridge, Cambridge, UK.
Richard J. Harrison
Affiliation:
Department of Earth Sciences, University of Cambridge, Cambridge, UK.
*
*Corresponding author: mb977@cam.ac.uk

Abstract

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Type
Leveraging 3D Imaging and Analysis Methods for New Opportunities in Material Science
Information
Microscopy and Microanalysis , Volume 25 , Supplement S2 , August 2019 , pp. 410 - 411
Copyright
Copyright © Microscopy Society of America 2019 

References

[1]Lascu, I et al. , Journal of Geophysical Research: Solid Earth 123 (2018), p. 7285.Google Scholar
[2]Hitzman, MW, Redmond, PB and Beaty, DW, Economic Geology 97 (2002), p. 1627.Google Scholar
[3]The authors acknowledge ZEISS for instrument access.Google Scholar