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Total variation(TV) regularization is applied to X-Ray computedtomography(CT) in an effort to reduce metal artifacts. Tikhonov regularizationwith $L^2$ data fidelity term and total variation regularization is augmentedin this novel model by inequality constraints on sinogram data affected bymetal to model errors caused by metal. The formulated problem is discretizedand solved using the Chambolle-Pock algorithm. Faster convergence is achievedusing preconditioning in a Douglas-Rachford spitting method as well as AdvancedDirection Method of Multipliers(ADMM). The methods are applied to real andsynthetic data demonstrating feasibility of the model to reduce metalartifacts. Technical details of CT data used and its processing are given inthe appendix.

TV-regularized CT Reconstruction and Metal Artifact Reduction Using Inequality Constraints with Preconditioning