title: Efficient CT metal artifact reduction based on fractional-order curvature diffusion.
abstract: We propose a novel metal artifact reduction method based on a fractional-order curvature driven diffusion model for X-ray computed tomography. Our method treats projection data with metal regions as a damaged image and uses the fractional-order curvature-driven diffusion model to recover the lost information caused by the metal region. The numerical scheme for our method is also analyzed. We use the peak signal-to-noise ratio as a reference measure. The simulation results demonstrate that our method achieves better performance than existing projection interpolation methods, including linear interpolation and total variation.
authors.affiliation: College of Computer Science, Sichuan University, Chengdu, China. maybe198376@gmail.com
authors.forename: Yi
authors.initials: Y
authors.lastname: Zhang
authors.forename: Yi-Fei
authors.initials: YF
authors.lastname: Pu
authors.forename: Jin-Rong
authors.initials: JR
authors.lastname: Hu
authors.forename: Yan
authors.initials: Y
authors.lastname: Liu
authors.forename: Qing-Li
authors.initials: QL
authors.lastname: Chen
authors.forename: Ji-Liu
authors.initials: JL
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D016477:Artifacts; D008962:Models, Theoretical; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D059629:Signal-To-Noise Ratio; D014057:Tomography, X-Ray Computed / Q000379:methods*