# On the Measurement of Particle Contact Curvature and Young's Modulus Using X-ray \(\mu\)CT
## 4 Experimental Protocol
### Data Acquisition and Image Conversion  
During the rotation of the X-ray scan, the projection image is generated by sequential capture of attenuated X-ray beams by the detector. For cone beam geometry, it requires projection images with equal angular separation between 0\({}^{\circ}\) and 360\({}^{\circ}\). The last image at 360\({}^{\circ}\) is called the short scan, which is not used for the reconstruction, but is used for the calculation of the rotation center. In terms of the number of projections herein, 1000 projections are collected in the cone beam geometry, which is deemed sufficient for the quality of reconstruction. Alignment of the scanning system is a prerequisite to ensure tomography acquisition with good quality. The beam axis should be aligned with the center of the detector. Image reconstruction is the mathematical process of converting raw data collected via data acquisition into two-dimensional slice images [35]. There are several methods to implement the reconstruction process such as analytical, iterative, back and filtered back projection. Amongst these, filtered back projection is the most widely used method. The advantage of filtered back projection is that blurring resulting from simple  
Figure 6: In-situ loading apparatus and X-ray scanning instrument a: X-ray source, b: barrel as displacement control mode, c: plastic pillar, d: rotary table, e: X-ray detector and f: meter reading.  
back projection can be mitigated with this method. In other words, a filter function is applied to each 2D attenuation profile before performing the back projection. The software utilized for image reconstruction is Octopus 8.0 [36], which was originally developed for neutron tomography. An Octopus dataset typically includes projection images (raw data), optionally beam profile images (flat images) and dark images (offset images). The reconstruction procedure based on the Octopus dataset is described below:  
1. Select the directory with projection images in Octopus and then input the beam profile image and dark images in turn (Figure 7). Then the scanning parameters of the cone beam mode are specified.  
2. After selecting the data in step 1, the original projections should be cropped with a desired region of interest (ROI) in Figure 8 so as to keep the data volume as small as possible. Then set up the value of the spot filter to eliminate white spots. Projection normalizing is performed to divide the projections by the beam profile images (flat images). Note that the selection of ROI for normalization should not be too close to the object, since the background radiation level can be influenced by the scattering of radiation from the object. A value of ring filter is then assigned to remove the rings artifact due to inappropriate behavior of pixels in the detector. With the option of sonogram ticked, the Start option is enabled to generate normalized images and sonograms.  
Figure 8: Selection of region of interest (ROI) to crop and normalize.  
Figure 7: Selection of projection images, open beam images and dark images in Octopus.  
3. The tomographic images are ready to output following image reconstruction and rescale in Figure 9.