/Beam-hardening-correction

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

Primary LanguageImageJ MacroOtherNOASSERTION

Beam hardening correction

Automated high accuracy, rapid beam hardening correction in X-Ray Computed Tomography of multi-mineral, heterogeneous core samples. Authors: Carla Romano, James M. Minto, Zoe K. Shipton, Rebecca J. Lunn. For info please email cromano3@wisc.edu

If you intend to use this work and distribute derivate works please cite: Romano, C., Minto, J. M., Shipton, Z. K., & Lunn, R. J. (2019). Automated high accuracy, rapid beam hardening correction in X-Ray Computed Tomography of multi-mineral, heterogeneous core samples. Computers & Geosciences, 131, 144-157. https://doi.org/10.1016/j.cageo.2019.06.009

This dataset contains beam hardening correction macros, running on ImageJ software. Requirements:

For running the code

  • Launch Fiji and load the image stack (File-Import-Image sequence)
  • Load the code in the software (Plugin-Macro-Edit) and click Run.
  • A dialogue box is shown as soon the code is running, requesting:
    • Top and bottom number slices on which the correction should be applied.
    • Width of outer ring (pixel). This is to crop out any material outside the sample, such as container or other external layers. If no outer ring is present put 0 as value. If the image is in a specific unit and not in pixel, please remove the scale(Analyze-Set scale- Click to Remove Scale) before running the code.
    • Tick the box if it's an internal or zoomed in scan.
    • Press ok.

All the following steps in the correction are completely automatic.

UPDATE March 2020

A new faster version of the code has been released. Please download "BeamHardening_Correction_plugin_CLIJ.ijm" file. GPU-accelerated by Robert Haase. In order to run the adapted version, activate the CLIJ and CLIJ2 update sites in your Fiji (check here how to https://clij.github.io/). Please cite also: Haase, R., Royer, L.A., Steinbach, P. et al. CLIJ: GPU-accelerated image processing for everyone. Nat Methods 17, 5–6 (2020). https://doi.org/10.1038/s41592-019-0650-1" For running properly the code please update to the latest versions of Clij and Clij2. Please also update Fiji ImageJ to the latest version as well (1.53k on 19/7/2021).