On the challenges of greyscale‐based quantifications using X‐ray computed microtomography

• Published in: Journal of microscopy (Oxford) Vol. 275; no. 2; pp. 82 - 96
• Main Authors: ZHANG, YULAI, MOSTAGHIMI, PEYMAN, ARMSTRONG, RYAN T.
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01.08.2019
• Subjects: Attenuation coefficients; Computation; Computed tomography; Computer simulation; Contrast agents; Desiccants; Diffusivity; Dynamic imaging; Error analysis; errors and uncertainties; Experiments; greyscale‐based quantification; Image acquisition; Image processing; Image resolution; Image segmentation; Linearity; Mathematical models; Morphology; pore‐scale simulation; Porosity; Porous media; Sandstone; Simulation; Three dimensional models; Uncertainty; X ray microtomography; X‐ray tomography; X-ray tomography; errors and uncertainties; Dynamic imaging; greyscale-based quantification; pore-scale simulation
• ISSN: 0022-2720; 1365-2818
• DOI: 10.1111/jmi.12805

Summary For X‐ray computed microtomography (μ‐CT) images of porous rocks where the grains and pores are not fully resolved, the greyscale values of each voxel can be used for quantitative calculations. This study addresses the challenges that arise with greyscale‐based quantifications by conducting experiments designed to investigate the sources of error/uncertainty. We conduct greyscale‐based calculations of porosity, concentration and diffusivity from various μ‐CT experiments using a Bentheimer sandstone sample. The dry sandstone is imaged overtime to test the variation of greyscale values over sequential scans due to instrumentation stability. The sandstone is then imaged in a dry and contrast‐agent saturated state at low resolution to determine a porosity map, which is compared to a porosity map derived from segmented high‐resolution data. Then the linearity of the relationship between the concentration of a contrast agent and its corresponding attenuation coefficient is tested by imaging various solutions of known concentration. Lastly, a diffusion experiment is imaged at low resolution under dynamic conditions to determine local diffusivity values for the sandstone, which is compared to values derived from direct pore‐scale simulations using high‐resolution data. Overall, we identify the main errors associated with greyscale‐based quantification and provide practical suggestions to alleviate these issues. Lay Description X‐ray computed microtomography (CT) imaging has become an important way to study the pore space of a porous medium. Using segmented images, we can build 3D pore space models for porous media and characterize the morphology and/or run simulations on the models. So, image segmentation is a critical image processing step. However, for low resolution images where image segmentation is not possible, grayscales are directly used for quantifications such as porosity and concentration calculations. Although these types of calculations have been widely accepted and used, the uncertainties and errors associated with grayscale‐based quantifications are not fully discussed. Here we specifically design experiments with X‐ray CT imaging to address the challenges that arise in grayscale‐based quantifications. For instance, in order to validate porosity calculation results from low resolution images (with the help of high attenuating tracer), high resolution images are also acquired, which serve as a benchmark. The errors associated with concentration calculation using grayscale values are also discussed. In addition, numerical simulations using grayscale values are performed on a diffusion experiment images with X‐ray CT. The problems that arise in dynamic imaging and the subsequent numerical simulations are discussed. The experiments, calculations and discussions provide a more comprehensive understanding on grayscale‐based quantifications and aid in designing better X‐ray CT experiments.