Comparison of Metal Artefact Reduction Algorithms from Medicine Applied to Industrial XCT Applications
C. Gusenbauer, M. Reiter, D. Salaberger, J. Kastner - Comparison of Metal Artefact Reduction Algorithms from Medicine Applied to Industrial XCT Applications - 19th World Conference on Non-Destructive Testing, WCNDT 2016 , München, Deutschland, 2016
Artefacts are mainly arising due to scattered radiation and polychromatic
nature of industrial X-ray sources which are typically used in X-ray computed
tomography (XCT) systems. Artefacts are especially dominant in the case of multimaterial
components consisting of low absorbing and metallic parts, which degrade
image quality and hinder e.g. proper segmentation, failure analysis or inspection of
State-of-the-art metal artefact reduction (MAR) methods are either using
iterative methods with prior knowledge or sinogram-based inpainting of the raw
projection data with deletion of metal traces (from e.g. implants) and the subsequent
interpolation of missing data. These approaches have already shown their usefulness
in clinical routine and diagnostics by reducing image noise or resolving small
structures beside metal parts. Since industrial parts are usually more complex, made
of multi-material components such as plastic housings with metal pins or conducting
paths made of iron or copper, an even stronger appearance of artefacts as compared
to medical data can be observed. Therefore some modifications may be applied to
the existing MAR methods.
This contribution shows results of sinogram-based correction methods applied
to real world parts as well as simulated XCT data from different industrial
applications with methodical modifications such as dual energy data as input.
Benefits and limitations will be discussed for each task and specimen regarding
artefact reduction, gain in information, detectability and image quality.