Physical Model-Based Metal Artifact Reduction (MAR) Scheme for a 3D Cone-Beam CT Extremity Imaging System

In Cone Beam CT Imaging, metallic and other dense objects, such as implantable orthopedic appliances, surgical clips and staples, and dental fillings, are often acquired as part of the image dataset. These high-density, high atomic mass objects attenuate X-rays in the diagnostic energy range much more strongly than soft tissue or bony structures, resulting in photon starvation at the detector. In addition, signal behind the metal objects suffer from increased quantum noise, scattered radiation, and beam hardening. All of these effects combine to create nonlinearities which are further amplified by the reconstruction algorithm, such as conventional filtered back-projection (FBP), producing strong artifacts in the form of streaking. They reduce image quality by masking soft tissue structures, not only in the immediate vicinity of the dense object, but also throughout the entire image volume. A novel, physical-model-based, metal-artifact reduction scheme (MAR) is proposed to mitigate the metal-induced artifacts. The metal objects are segmented in the projection domain, and a physical model based method is adopted to fill in the segmented area. The FDK1 reconstruction algorithm is then used for the final reconstruction.