X-ray computed tomography (XCT) is a fast-growing technology for dimensional measurements in industrial applications. However, traceable and efficient methods to determine measurement uncertainties are not available. Guidelines like the VDI/VDE 2630 Part 2.1 suggest at least 20 repetitions of a specific measurement task, which is not feasible for industrial standards. Simulation-based approaches to determine task specific measurement uncertainties are promising, but require closely adjusted model parameters and an integration of error sources like geometrical deviations during a measurement. Unfortunately, the development of an automated process to parameterize and integrate geometrical deviations into XCT models is still an open issue. In this work, the whole processing chain of dimensional XCT measurements is taken into account with focus on the issues and requirements to determine suitable parameters of geometrical deviations. Starting off with baseline simulations of different XCT systems, two approaches are investigated to determine and integrate geometrical deviations of reference measurements. The first approach tries to iteratively estimate geometric deviation parameter values to match the characteristics of the missing error sources. The second approach estimates those values based on radiographs of a known calibrated reference object. In contrast to prior work both approaches only use a condensed set of parameters to map geometric deviations. In case of the iterative approach, some major issues regarding unhandled directional dependencies have been identified and discussed. Whereas the radiographic method resulted in task specific expanded measurements uncertainties below one micrometre even for bi-directional features, which is a step closer towards a true digital twin for uncertainty estimations in dimensional XCT.

Article Digital Laminography was published on June 1, 1995 in the journal Materials Testing (volume 37, issue 6).

For the long-term goal of determining the measurement uncertainty of dimensional computed tomography (CT) measurements with simulation, it is necessary to prove the compatibility of the digital model with its real counterpart. A study of repeated CT measurements of a calibrated aluminum specimen was performed and afterwards simulated. A first indicator for a sufficiently good digital representation is the agreement of dimensional measurands, such as diameters and center-to-center distances. Results show in general good agreement between simulation and real measurement. A detailed discussion of the results as well as a proposed criterion for testing the simulation will be shown in the full paper.

The purpose of the 2014 WFNDEC RT benchmark study was to compare predictions of various models of radiographic techniques, in particular those that predict the contribution of scattered radiation. All calculations were carried out for homogenous materials and a mono-energetic X-ray point source in the energy range between 100 keV and 10 MeV. The calculations were to include the best physics approach available considering electron binding effects. Secondary effects like X-ray fluorescence and bremsstrahlung production were to be taken into account if possible. The problem to be considered had two parts. Part I examined the spectrum and the spatial distribution of radiation behind a single iron plate. Part II considered two equally sized plates, made of iron and aluminum respectively, only evaluating the spatial distribution. Here we present the results of above benchmark study, comparing them to MCNP as the assumed reference model. The possible origins of the observed deviations are discussed.

This study reports a strategy to use sophisticated, realistic X-ray Computed Tomography (CT) simulations to reduce Missing Wedge (MW) and Region-of-Interest (RoI) artifacts in FBP (Filtered Back-Projection) reconstructions. A 3D model of the object is used to simulate the projections that include the missing information inside the MW and outside the RoI. Such information augments the experimental projections, thereby drastically improving the reconstruction results. An X-ray CT dataset of a selected object is modified to mimic various degrees of RoI and MW problems. The results are evaluated in comparison to a standard FBP reconstruction of the complete dataset. In all cases, the reconstruction quality is significantly improved. Small inclusions present in the scanned object are better localized and quantified. The proposed method has the potential to improve the results of any CT reconstruction algorithm.

In modern CT imaging, simulation has become an important tool to minimize cost- and time-intensive measurements. It is increasingly used to optimize techniques for complex applications, to support the preparation of written procedures, and for educational purposes. We extended the CT simulation software ‘aRTist’ with a module to set-up arbitrary trajectories including disturbing influences during the scan. Moreover, such geometric deviations can be compensated by the internal reconstruction tool.