High contrast artifact reduction in Cone Beam Computed Tomography by using Geometric Techniques

The use of cone beam computed tomography (CBCT) is growing in the clinical arena, due to its ability to provide 3-D information during interventions, its high diagnostic quality (sub-millimeter resolution), and its short scanning times (10 seconds). In many situations, the reconstructions suffer from artifacts from high contrast objects (due mainly to angular sampling by the projections or by beam hardening) which can reduce image quality. In this study, we propose a novel algorithm to reduce these artifacts. In our approach, these objects are identified and then removed in the sinogram space by using computational geometry techniques. In particular, the object is identified in a reconstruction from a few views. Then, the rays (projection lines) intersecting the high contrast objects are identified using the technique of topological walk in a dual space which effectively models the problem as a visibility problem and provides a solution in optimal time and space complexity. As a result, the corrections can be performed in real time, independent of the projection image size. Subsequently, a full reconstruction is performed by leaving out the high contrast objects in the reconstructions. Evaluations were performed using simulations and animal studies. The artifacts are significantly reduced when using our approach. This optimal time and space complexity and relative simple implementation makes our approach attractive for artifact reduction.