On the use of voxel-driven backprojection and iterative reconstruction for small ROI CT imaging

Abstract

In this work related to the use of a commercial medical CT scanner for the non-destructive analysis of highly attenuating materials (mineral samples), the effect of backprojection techniques and truncation artifacts corrections were explored. For small ROIs, the CT couch interferes significantly in images of small samples (few centimeters). An iterative reconstruction algorithm (OSC-TV) was used to perform reconstructions from uncorrected raw projection data made available through a collaboration with the CT vendor, who provided binaries and methods to remove low-level, proprietary data corrections (for beam hardening). The OSC-TV algorithm is customizable, allowing for the use of different forward-projection and backprojection techniques. Reconstruction parameters were tuned by performing simulations in a virtual phantom involving highly attenuating materials. Strategies to reconstruct small ROIs were also explored, with the objective of reducing truncation artifacts. Three samples were scanned to compare a ray-driven backprojection and a voxel-driven backprojection technique based on bilinear interpolation. The voxel-driven approach led to better results in terms of noise and reconstruction artifacts. An iterative ROI reconstruction technique was used to reconstruct small ROIs. This technique allows obtaining a sinogram with the projections of the ROI only. With that, truncation artifacts were reduced, which led to images with less blurring.

Tomographic reconstruction strategies for nondestructive testing with a commercial CT scanner

“…Due to the small size of the sandstone and the small voxel sizes used in the respective tomographic reconstructions (Figure 7), the separation of adjacent rays is large compared to the voxel size Hahn et al (2016), so some voxels are missed during the raytracing in the backprojection. As not all voxels are incremented by the correspondent detector read, more artifacts arise, producing a poor quality image, however, with no truncation artifacts Trotta et al (2022), whereas (b) suffers from both artifacts. Finally, in (d), both IR ROI and voxel-driven with bilinear interpolation are combined.…”

“…With proprietary beam-hardening corrections neutralized, one is able to apply custom methods to mitigate such artifacts and take into account the properties of various materials for the correction (such as dense minerals and metals). Here, the method developed by Trotta et al (2022) Di Schiavi Trotta et al (2022), OSC-TV-poly, was applied to show how images with reduced artifacts can be obtained (see Table 4). The calibration curve, bowtie filter model, Xray spectra and detector response were the same as in the cited paper for the case where the tube voltage was set at 140 kVp Di Schiavi Trotta et al (2022).…”