In conventional industrial computed tomography, thesource–detector system rotates in equiangular stepsin-plane relative to the part of investigation. Whilebeing by far the most frequently used acquisitiontrajectory today, this method has several drawbackslike the formation of cone beam artefacts or limitedusability in case of geometrical restrictions. In suchcases, the usage of alternative spherical trajectoriescan be beneficial to improve image quality and defectvisibility. While investigations have been performedto relate the influence of the trajectory choice in thetypical metrological case of a high number of availableprojections, so far barely any work has been donefor the case of few source–detector poses, which ismore relevant in the field of non-destructive testing.In this work, we provide an overview of quantitativemetrics that can be used to assess the image qualityof reconstructed computed tomography volumes,discuss their advantages and drawbacks and proposea framework to investigate the performance of severalnon-standard trajectories with respect to previouslydefined regions of interest. Inspired by pseudorandomsampling methods for Monte–Carlo-algorithms, wealso suggest an entirely new trajectory design, thelow-discrepancy spherical trajectory, which extendsthe concept of equiangular planar trajectories intothree dimensions and can be used for benchmarkingand comparison with other spherical trajectories.Last, we use an optimization method to calculatetask-specific acquisition trajectories and relate theirperformance to other spherical designs.
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In conventional industrial computed tomography, thesource–detector system rotates in equiangular stepsin-plane relative to the part of investigation. Whilebeing by far the most frequently used acquisitiontrajectory today, this method has several drawbackslike the formation of cone beam artefacts or limitedusability in case of geometrical restrictions. In suchcases, the usage of alternative spherical trajectoriescan be beneficial to improve image qual...
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