14-17 May 2018
New Orleans
US/Central timezone

Automated high accuracy, rapid beam hardening correction in X-Ray Computed Tomography of multi-mineral, heterogeneous core samples

15 May 2018, 17:15
1h 30m
New Orleans

New Orleans

Poster MS 2.06: New Trends in Image Processing: From Discrete Tomography over Machine Learning to in-situ Contact Angle Measurement Poster 2


Dr Carla Romano (University of Strathclyde)


X-ray Computed Tomography scanning is an innovative procedure that allows the internal structure of samples to be computed in 3D. It has completely revolutionized the way several measurements can be achieved in geoscience, including characterization of petrophysical properties of porous media. In order to provide accurate results, it is, of course, necessary to have high quality scan images, free of artefacts. One of the most problematic artefacts is beam hardening, which, in cylindrical shapes, increases the attenuation values with increasing distance from the centre. Until now, no automatic solution has been proposed for cylindrically-shaped cores that is both computationally feasible and applicable to all geological media. A new technique is here introduced for correcting the beam hardening, using a linearization procedure of the beam hardening curve applied after the reconstruction process. We have developed an automated open source plug-in, running on ImageJ software, which does not require any a priori knowledge of the material, distance from the source or the scan conditions (current, energy), nor any segmentation of phases or calibration scan on phantom data. It is suitable for expert and non-expert use, alike. We have tested the technique on μCT scan images of a plastic rod, a sample of loose sand, several heterogeneous sandstone core samples (with near-cylindrical shapes), and finally, on an internal scan of a Berea sandstone core. This last sample was also scanned using a medical X-CT scanner with a fan-beam geometry, as opposed to a cone beam geometry, showing that our algorithm is equally effective in both cases. Our correction technique successfully removes the beam hardening artefact in all cases, as well as removing the cupping effect common to internal scans. For a Berea Sandstone, which varies in porosity from 19%-20%, porosity calculated using the corrected scan is 20.54%, which compares to a value of 14.24% using the software provided by the manufacturer.


Biguri, A., Dosanjh, M., Hancock, S., and Soleimani, M. (2016). TIGRE: a MATLAB-GPU toolbox for CBCT image reconstruction. Biomedical Physics and Engineering Express, 2(5), 055010.
Carl, P. (2006). Radial Profile Extended. [online] Available at: https://imagej.nih.gov/ij/plugins/radial-profile-ext.html
Cnudde, V., and Boone, M. N. (2013). High-resolution X-ray computed tomography in geosciences: A review of the current technology and applications. Earth-Science Reviews, 123, 1-17.
Feldkamp, L. A., Davis, L. C., & Kress, J. W. (1984). Practical cone-beam algorithm. JOSA A, 1(6), 612-619.
Gilbert, P. (1972). Iterative methods for the three-dimensional reconstruction of an object from projections. Journal of theoretical biology, 36(1), 105-117.
Jennings, R. J. (1988). A method for comparing beam‐hardening filter materials for diagnostic radiology. Medical physics, 15(4), 588-599.
Joseph, P. M., & Spital, R. D. (1981). The exponential edge-gradient effect in x-ray computed tomography. Physics in medicine and biology, 26(3), 473.
Jovanović, Z., Khan, F., Enzmann, F., and Kersten, M. (2013). Simultaneous segmentation and beam-hardening correction in computed microtomography of rock cores. Computers and Geosciences, 56, 142-150.
Kachelrieß, M., Sourbelle, K., and Kalender, W. A. (2006). Empirical cupping correction: A first‐order raw data precorrection for cone‐beam computed tomography. Medical physics, 33(5), 1269-1274.
Ketcham, R. A., & Hanna, R. D. (2014). Beam hardening correction for X-ray computed tomography of heterogeneous natural materials. Computers & geosciences, 67, 49-61.
Krevor, S., Pini, R., Zuo, L., and Benson, S. M. (2012). Relative permeability and trapping of CO2 and water in sandstone rocks at reservoir conditions. Water Resources Research, 48(2).
Kruth, J. P., Bartscher, M., Carmignato, S., Schmitt, R., De Chiffre, L., and Weckenmann, A. (2011). Computed tomography for dimensional metrology. CIRP Annals-Manufacturing Technology, 60(2), 821-842.
Lager, A., Webb, K. J., Black, C. J. J., Singleton, M., & Sorbie, K. S. (2008). Low salinity oil recovery-an experimental investigation1. Petrophysics, 49(01).
Lechuga, L., & Weidlich, G. A. (2016). Cone Beam CT vs. Fan Beam CT: A Comparison of Image Quality and Dose Delivered Between Two Differing CT Imaging Modalities. Cureus, 8(9).
Li, C. H., and Lee, C. K. (1993). Minimum cross entropy thresholding. Pattern recognition, 26(4), 617-625.
Minto, J.M., Hingerl, F., Benson, S.M., Lunn, R.J., 2017a. X-ray CT and multiphase flow characterization of a “bio-grouted” sandstone core: the effect of dissolution on seal longevity. Int. J. Greenh. Gas Control 64, 152–162. doi:10.1016/j.ijggc.2017.07.007
Minto, J.M., Lunn, R.J., El Mountassir, G., Guo, H., Cheng, X., 2017b. “Microbial Mortar”- restoration of degraded marble structures with microbially induced carbonate precipitation. Manuscript submitted for publication.
Mooney, S. J., Pridmore, T. P., Helliwell, J., & Bennett, M. J. (2012). Developing X-ray computed tomography to non-invasively image 3-D root systems architecture in soil. Plant and soil, 352(1-2), 1-22.
Mooney, S. J. (2002). Three‐dimensional visualization and quantification of soil macroporosity and water flow patterns using computed tomography. Soil Use and Management, 18(2), 142-151.
Pauwels, R., Araki, K., Siewerdsen, J. H., & Thongvigitmanee, S. S. (2014). Technical aspects of dental CBCT: state of the art. Dentomaxillofacial Radiology, 44(1), 20140224.
Perrin, J. C., Krause, M., Kuo, C. W., Miljkovic, L., Charoba, E., & Benson, S. M. (2009). Core-scale experimental study of relative permeability properties of CO2 and brine in reservoir rocks. Energy Procedia, 1(1), 3515-3522.
Pini, R., Krevor, S. C., & Benson, S. M. (2012). Capillary pressure and heterogeneity for the CO2/water system in sandstone rocks at reservoir conditions. Advances in Water Resources, 38, 48-59.
Ritschl, L., Bergner, F., Fleischmann, C., & Kachelrieß, M. (2010). Water calibration for CT scanners with tube voltage modulation. Physics in medicine and biology, 55(14), 4107.
Shipton Z.K., Evans J. P., Robeson K., Forster C. B. and Snelgrove S. 2002. Structural heterogeneity and permeability in faulted eolian sandstone: implications for subsurface modelling of faults. American Association of Petroleum Geologists Bulletin, 86, 863-883.
Van Geet, M., Swennen, R., & Wevers, M. (2000). Quantitative analysis of reservoir rocks by microfocus X-ray computerised tomography. Sedimentary Geology, 132(1), 25-36.
Wellington, S. L., & Vinegar, H. J. (1987). X-ray computerized tomography. Journal of Petroleum Technology, 39(08), 885-898.
Yang, Q., Maass, N., Tian, M., Elter, M., Schasiepen, I., Maier, A., & Hornegger, J. (2013). Multi-material beam hardening correction (mmbhc) in computed tomography. In Proc. Intl. Mtg. on Fully 3D Image Recon. in Rad. And Nuc. Med (pp. 533-536).

Acceptance of Terms and Conditions Click here to agree

Primary author

Dr Carla Romano (University of Strathclyde)


Dr James Minto (University of Strathclyde) Prof. Zoe K. Shipton (University of Strathclyde) Prof. Rebecca J. Lunn (University of Strathclyde)

Presentation Materials

There are no materials yet.