%0 Journal Article %1 herl2020scanning %A Herl, Gabriel %A Hiller, Jochen %A Maier, Andreas %D 2020 %J Nondestructive Testing and Evaluation %K gher %N 3 %P 287-303 %R 10.1080/10589759.2020.1774579 %T Scanning trajectory optimisation using a quantitative Tuybased local quality estimation for robot-based X-ray computed tomography %V 35 %X Robotic CT systems allow complex scanning trajectories. This work presents a workflow to automatically calculate optimised scanning trajectories for robotic CT systems. In particular, as a local quality estimation, this work introduces a quantitative measure to quantify local reconstruction quality based on the Tuy conditions. The proposed method is tested in two summation experiments using an STL model of a motorcycle. In both experiments, a trajectory is calculated using a quantitative Tuy-based local quality estimation and the reconstruction result is then compared to reconstructions using conventional scanning trajectories. The comparison results indicate that the proposed approach automatically finds trajectories that enable 3D reconstructions with high image quality using much less projection data, which allows a significant reduction of scanning time.

@article{herl2020scanning, abstract = {Robotic CT systems allow complex scanning trajectories. This work presents a workflow to automatically calculate optimised scanning trajectories for robotic CT systems. In particular, as a local quality estimation, this work introduces a quantitative measure to quantify local reconstruction quality based on the Tuy conditions. The proposed method is tested in two summation experiments using an STL model of a motorcycle. In both experiments, a trajectory is calculated using a quantitative Tuy-based local quality estimation and the reconstruction result is then compared to reconstructions using conventional scanning trajectories. The comparison results indicate that the proposed approach automatically finds trajectories that enable 3D reconstructions with high image quality using much less projection data, which allows a significant reduction of scanning time.}, added-at = {2021-02-03T14:11:34.000+0100}, author = {Herl, Gabriel and Hiller, Jochen and Maier, Andreas}, biburl = {https://www.bibsonomy.org/bibtex/2c4a2b56e8327cb9fe79b03e3baa609d6/baywiss1}, doi = {10.1080/10589759.2020.1774579}, interhash = {1d2f758609bc2363aa4cd74b5303e1f0}, intrahash = {c4a2b56e8327cb9fe79b03e3baa609d6}, journal = {Nondestructive Testing and Evaluation}, keywords = {gher}, number = 3, pages = {287-303}, timestamp = {2021-02-03T14:11:34.000+0100}, title = {Scanning trajectory optimisation using a quantitative Tuybased local quality estimation for robot-based X-ray computed tomography}, volume = 35, year = 2020 }