Penalized-likelihood reconstruction for metal artifact reduction in cone-beam CT.
CT reconstruction from metal-embedded data usually produces streak artifacts that reduce the quality of the reconstructed images. In this paper, we propose a new technique for metal artifact reduction in cone-beam CT based on statistical reconstruction. First, the metal objects are segmented in the reconstructed images and then reprojected to obtain the measurement data of the metal objects using cone-beam reconstruction. The original measurement data in the metal area are corrected through cubic interpolation. y, the corrected measurement data are reconstructed with the penalized likelihood using the modified convex algorithm. The simulation results show that the reconstructed images of the metal object using the proposed metal artifact reduction technique are superior to conventional filtered backprojection reconstruction.
Aootaphao
Sorapong
S
Department of Electronics, Faculty of Engineering, and Research Center for Communications and Technology, King Mongkut's Institute of Technology Ladkrabang, Thailand. akeandjoy@hotmail.com
Pintavirooj
Chuchart
C
Sotthivirat
Saowapak
S
D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016013:Likelihood Functions; D015233:Models, Statistical; D009038:Motion; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D015656:Respiratory Mechanics; D012680:Sensitivity and Specificity