Fast iterative algorithm for metal artifact reduction in X-ray CT

Rationale and Objectives. The reduction of metal artifacts in x-ray compute d tomography (CT) has important clinical applications. An iterative method adapted from the expectation maximization (EM) formula for emission CT was shown to be effective for metal artifact reduction, but its computational s peed is slow. The goal of this project was to accelerate that iterative met hod for metal artifact reduction. Materials and Methods. Using the row-action/ordered-subset (EM) formula for emission CT as a basis, the authors developed a fast iterative algorithm f or metal artifact reduction. In each iteration of this algorithm, both repr ojection from an intermediate image and backprojection from discrepancy dat a are performed, Results. The feasibility of the fast iterative algorithm was demonstrated i n numerical and phantom experiments. In comparison with the nonaccelerated iterative algorithm, the speed of iterative metal artifact reduction is imp roved by an order of magnitude given image quality in terms of visual inspe ction, I-divergence in the projection domain, and the euclidean distance in the image domain. Conclusion. The fast iterative algorithm corrects intermediate reconstructi on according to subsets of projections and produces satisfactory image qual ity at a much faster speed than the previously published iterative algorith m. This algorithm has important potential in clinical applications, such as orthopedic, oncologic, and dental imaging.