This work applies Bayesian experimental design to selecting optimal projection geometries in (discretized) parallel beam X-ray tomography assuming the prior and additive noise are Gaussian. The introduced greedy exhaustive optimization algorithm proceeds sequentially, with posterior distribution corresponding previous projections serving as for determining parameters, i.e. imaging angle lateral...