Author:

Abstract:

Cone-beam computed tomography (CT) with circular scanning trajectory is known to suffer from so called cone-beam artifacts. Cone-beam artifacts are errors in the reconstructed volume due to incomplete radon data. These artifacts increase with increasing distance of the reconstructed plane from the midplane, i.e. the plane containing the X-ray source. Theoretically, the midplane represents the ideal data set for tomographic reconstruction as the entire set of line integrals, i.e. the X-ray attenuation trajectories, are parallel to the plane they are used to reconstruct. The angle between the reconstructed plane and the line integrals used to reconstruct it increases with increasing distance from the midplane. Cone-beam artifacts generally result in a degradation of tomographically reconstructed edges, subsequently affecting dimensional measurements. Appearance of cone-beam artifacts depends on the position and orientation of the object under investigation in the measurement volume. In this paper we propose an algorithm that takes as an input the triangulated surface, e.g. a CAD model, of a scanned object and predicts where the object's surface cannot be reconstructed properly due to cone-beam artifacts. We apply Tuy's data sufficiency condition to define the analytical relationship between each surface triangle in the object model and the ability to reconstruct it using circular scan CT. The output of the proposed algorithm is the object position and orientation that reduces the effects of cone beam artifacts. The proposed algorithm is highly parallelizable and provides computational benefits when compared to conventional CT simulation methods. Operators of CT can use the proposed algorithm to reduce the influence of the cone-beam artifact on the measurements results.