Parametric boundary reconstruction algorithm for industrial CT metrology application

Abstract

High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object.In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly incorporated as prior knowledge to improve the convergence of an iterative approach. In this paper, the feasibility of parametric boundary reconstruction algorithm is demonstrated with both simple and complex simulated objects. Finally, the proposed algorithm is applied to the experimental industrial CT system data.

Assessment of Knee Implant Alignment Using Coordinate Measurement on Three-Dimensional Computed Tomography Reconstructions

“…Generally, the 3D accuracy of CT systems is influenced by varying underlying physical processes such as scatter, beam hardening, off-focal radiation, detector point spread function, and partial volume effects. 20 Various methods have been developed for standardization and optimization of 3D CT measurements, for example, matrix transformation in the 3D coordinate system 21 or use of a parametric boundary reconstruction algorithm. 20 With CT, a point density is generated that is not attained by other measurement technologies.…”

“…20 Various methods have been developed for standardization and optimization of 3D CT measurements, for example, matrix transformation in the 3D coordinate system 21 or use of a parametric boundary reconstruction algorithm. 20 With CT, a point density is generated that is not attained by other measurement technologies. Compared with conventional CM machines, the CT-based CM individual minimum and maximum measurements are smaller and larger, respectively.…”