Least squares based geometric error measurement for sparse view CT: a 2D simulation study

Abstract

Abstract X-ray computed tomography (CT) is considered as one of the most common techniques in non-destructive testing and is also an essential and important method in the field of dimensional measurement. For high-precision measurement task scenarios, geometric errors due to the instability of the CT motion equipment cannot be ignored and need to be accurately measured and corrected. In-situ testing of large objects such as geotechnical materials, mechanical assemblies, metal weldments and concrete specimens also requires high-precision CT imaging of their interiors to obtain information of interest. The rotation of the scanning parts for these large in-situ tests and sparse-view scanning mode also makes it difficult to measure geometric errors. This paper therefore proposes a method for simultaneous measurement of geometric errors based on a priori information for in-situ testing characteristics. This method is capable of measuring geometric errors in sparse view projections with a length accuracy of 0.1 mm and an angular accuracy of 6 × 10 − 5 radians in 0.5 seconds per angle, as the simulation results show. The reconstruction results show that this level of geometric error measurement accuracy provides a dimensional measurement accuracy of 0.01 mm for the internal structure. The data for the simulation experiments in this paper are generated from real concrete data by noisy simulation.