P2-4. X-Ray Scatter Correction for Metallic Additive Manufacturing Inspection

Project leader: Andrew Kingston (Applied Maths, RSPhys ANU)
Industry partner: Jonathan Miller, DSTG
Fig. 1: The effect of X-ray scatter on tomography of a metal component.
(L) Image with scatter artefacts; (R) Result after correction with beam-stop-array.
(Image from Peterzol et al. Nucl. Instrum. Methods Phys. Res., B, 266, no.18 (2008): 4042-4054.)
  1. Benchmark current state-of-the-art 3D imaging capabilities for printed metal components. Require high quality for safety critical NDTE.
  2. Identify sources (non-ideal X-ray interactions) causing the most significant artefacts when imaging printed metal components.
  3. Develop techniques to reduce these most significant artefacts when imaging printed metal components.
Alignment within M3D Innovation:
  1. Enhance 3D imaging capabilities of highly attenuating/scattering samples, e.g., mining, implants, fossils.
  1. Incorporate non-ideal X-ray interactions (beam-hardening, scatter, photon starvation) into iterative reconstruction framework. This involves developing a model for each phenomenon and estimating the effect of these interactions in the forward model.
  2. Design a collimator to reject as much secondary radiation (X-ray scatter) as possible. Construct with highly attenuating material, e.g., tungsten, steel, nickel. Produce by 3D printing.
  3. Measure/estimate residual scatter through the use of a beam-stop-array or similar. The scatter can be measured directly behind a highly attenuating feature; the total can scatter can be estimated by extra/interpolation of these measured data points and removed.
Key Milestones:
  1. Complete state-of-the-art imaging series to determine benchmark capabilities.
  2. Incorporate spectrum and beam-hardening into forward model of iterative tomographic reconstruction (ITR) algorithm.
  3. Modify ITR algorithm to assume a Poisson noise model and deal with low/zero-photon counts.
  4. Design and implement collimator to reject X-ray scatter.
  5. Develop scatter measurement technique.
  6. Incorporate scatter model into forward model ITR algorithm.