Amirkhanov, A., Heinzl, C., Reiter, M., Kastner, J., & Gröller, E. (2011). Projection-Based Metal-Artifact Reduction for Industrial 3D X-ray Computed Tomography. IEEE Transactions on Visualization and Computer Graphics, 17(12), 2193–2202. https://doi.org/10.1109/tvcg.2011.228
IEEE Transactions on Visualization and Computer Graphics
Number of Pages:
Institute of Electrical and Electronics Engineers (IEEE)
Software; Computer Graphics and Computer-Aided Design; Computer Vision and Pattern Recognition; Signal Processing
Multi-material components, which contain metal parts surrounded by plastic materials, are highly interesting for inspection using industrial 3D X-ray computed tomography (3DXCT). Examples of this application scenario are connectors or housings with metal inlays in the electronic or automotive industry. A major problem of this type of components is the presence of metal, which causes streaking artifacts and distorts the surrounding media in the reconstructed volume. Streaking artifacts and dark-band artifacts around metal components significantly influence the material characterization (especially for the plastic components). In specific cases these artifacts even prevent a further analysis. Due to the nature and the different characteristics of artifacts, the development of an efficient artifact-reduction technique in reconstruction-space is rather complicated. In this paper we present a projection-space pipeline for metal-artifacts reduction. The proposed technique first segments the metal in the spatial domain of the reconstructed volume in order to separate it from the other materials. Then metal parts are forward-projected on the set of projections in a way that metal-projection regions are treated as voids. Subsequently the voids, which are left by the removed metal, are interpolated in the 2D projections. Finally, the metal is inserted back into the reconstructed 3D volume during the fusion stage. We present a visual analysis tool, allowing for interactive parameter estimation of the metal segmentation. The results of the proposed artifact-reduction technique are demonstrated on a test part as well as on real world components. For these specimens we achieve a significant reduction of metal artifacts, allowing an enhanced material characterization.
Visual Computing and Human-Centered Technology: 100%