With the advent of robotic C-arm computed tomography (CT) systems in medicine and twin-robotic CT systems in industry, new possibilities for the realisation of complex trajectories for CT scans are emerging. These trajectories will increase the range of CT applications, enable optimisation of image quality for many applications and open up new possibilities to reduce scan time and radiation dose. In this work, trajectory optimisation methods for optimising both, task-based data quality and data completeness, are presented by combining two different metrics. On the one hand, task-based data quality is optimised with a proven observer model. On the other hand, a Tuy-based metric is utilised to optimise data completeness. Both metrics capture mutually exclusive properties of the trajectory which are necessary, but alone are not sufficient for trajectory optimisation. Hence, existing task-driven trajectory optimisation approaches require additional input to decide on an overall optimal trajectory, e.g. in most cases constraints on the trajectory. Advantages and disadvantages of the presented methods are investigated. It is shown that by combining both metrics, trajectory optimisation for arbitrary geometries becomes possible. In application examples it is shown that this can be used for trajectory optimisation of challenging scanning tasks involving metal parts as well as for trajectory optimisation to reduce the number of projections while ensuring task-dependently high image quality. In total, the results of this work enable new applications for X-ray CT, especially for twin-robotic CT systems which are able to benefit from a high number of degrees of freedom.

Twin robotic X-ray computed tomography (CT) refers to CT systems in which two robotic arms are used to independently move the X-ray source and the X-ray detector around the object. This setup enables flexible CT scans by using robots to move the X-ray source and the X-ray detector around an object’s region of interest. This allows scans of large objects, image quality optimization and scan time reduction. Despite these advantages, robotic CT systems still face challenges that limit their widespread adoption. This paper discusses the state of twin robotic CT and its current main challenges. These challenges include the optimization of scanning trajectories, precise geometric calibration and advanced 3D reconstruction techniques.

CT systems with high degrees of freedom such as robot-guided setups allow CT scanning with arbitrary 3D trajectories. However, many existing systems require an additional calibration scan to determine the exact source/detector poses of new trajectories. I....

Industrial x-ray computed tomography (CT) systems with high geometric flexibility are increasingly utilized for large-scale measurement objects or challenging measurement tasks. To maintain high accuracy when deviating from the established circular scan trajectory, trajectory calibration methods using multi-sphere reference objects with known marker positions are commonly employed. These multi-sphere objects can either be scanned together with the measurement object (online trajectory calibration) or in a separate scan (offline trajectory calibration). While offline calibration increases machine time, it generally results in higher scan quality. However, a sufficient pose repeatability is necessary to ensure comparable or even superior accuracy to online calibration. In this contribution, we present a straightforward procedure to compare both types of trajectory calibration in a way that the differences of the results can directly be traced back to the influence of the pose repeatability. The multi-sphere reference object is not only used for trajectory calibration, but simultaneously as a measurement object for repeated measurements. The methodology is tested on both a twin robotic CT system and a conventional CT system that is additionally equipped with a hexapod manipulator for adaptive object tilting. Results showed, independent from the type of trajectory calibration, systematic measurement errors in the order of 10⁻⁵–10⁻⁴ of measured sphere distances and sphericity values below 50 μ m . For sphere distances, random errors were increased by a factor of 5 due to the offline trajectory calibration, but were still low ( < 1 μ m ) in comparison to systematic errors and the spread of different measurement features. Overall, both investigated systems demonstrated sufficient positioning repeatability for offline trajectory calibration. The method is in general also applicable to any other types of manipulator systems used for CT devices. It provides a workflow for the decision which type of trajectory calibration is preferable for a given CT system.

Twin robotic X-ray computed tomography (CT) systems enable flexible CT scans by using robots to move the X-ray source and the X-ray detector around an object’s region of interest. This allows scans of large objects, image quality optimization and scan time reduction. Despite these advantages, robotic CT systems still face challenges that limit their widespread adoption. This paper discusses the state of twin robotic CT and its current main challenges. These challenges include optimization of scanning trajectories, precise geometric calibration and advanced 3D reconstruction techniques.

Twin robotic computed tomography (RoboCT) offers a high degree of flexibility. RoboCT systems are commonly used for either flexible 2D inspection of large areas or 3D inspection of small areas in large objects. This study introduces a workflow to perform ....