In this paper, we derive a powerful algorithm for estimating missing line integrals in limited data computed tomography. We have formulated the estimation problem of missing line integrals in Radon space by the theory of projection onto convex sets (POCS) and utilized the Helgason-Ludwig consistency condition as a constraint in Radon space. Further, in order to stabilize the estimation process, we have used a priori knowledge about the rough shape of the object to be imaged. In the numerical experiments, it was confirmed that our method is superior to the previously reported algorithms from the view point of the computational cost and the image quality.
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