  Algebraic models for the reconstruction problem in X-ray computed tomography
(CT) provide a flexible framework that applies to many measurement geometries.
For large-scale problems we need to use iterative solvers, and we need stopping
rules for these methods that terminate the iterations when we have computed a
satisfactory reconstruction that balances the reconstruction error and the
influence of noise from the measurements. Many such stopping rules are
developed in the inverse problems communities, but they have not attained much
attention in the CT world. The goal of this paper is to describe and illustrate
four stopping rules that are relevant for CT reconstructions.
