Scanning trajectory optimisation using a quantitative Tuybased local quality estimation for robot-based X-ray computed tomography

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.

KEYWORDS:

• Computed tomography
• trajectory optimisation
• local quality estimations
• Tuy conditions
• image quality

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was part of the projects “MultiPosCT” and “Big Picture” which were funded by the “Bayerisches Staatsministerium für Wissenschaft und Kunst” (as part of the “Strukturimpuls Forschungseinstieg 2017”) and the “Bayerisches Wirtschaftsministerium”.