Computed Tomography (CT) is a common tool for internal inspection of objects in nondestructive testing. Currently, in industrial CT standard trajectories, e.g., 2D circular, in combination with filtered backprojection reconstruction algorithms are almost exclusively used. The increased availability of high performance hardware, e.g. GPUs, facilitates the revival of iterative reconstruction algorithms, which inherently support arbitrary trajectories. Previous work of others demonstrated that not all directions contribute equally to the reconstructed image. To exploit the new flexibility of iterative reconstruction methods, it is reasonable to move from standard trajectories to trajectories that include valuable projections and exclude less valuable projections. With respect to industrial applications the definition of valuable projections and trajectories is of high interest due to a wider range of materials and forms compared to medical applications. In this contribution, the image quality is improved and the scan time reduced by optimizing the trajectory. In many industrial CT applications prior knowledge of an object is available and, for example, a CAD-model of the object could be used as such prior information. The CAD data will be utilized to find valuable projections leading to an optimal trajectory. It is shown from simulations and experiments that the proposed method improves reconstruction results qualitatively and quantitatively.
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Computed Tomography (CT) is a common tool for internal inspection of objects in nondestructive testing. Currently, in industrial CT standard trajectories, e.g., 2D circular, in combination with filtered backprojection reconstruction algorithms are almost exclusively used. The increased availability of high performance hardware, e.g. GPUs, facilitates the revival of iterative reconstruction algorithms, which inherently support arbitrary trajectories. Previous work of others demonstrated that not...
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