Accurate estimation of local impurity concentrations is crucial for operation and control of fusion plasmas. For this we have developed a tomographic reconstruction technique using Bayesian inference. Combined with density and temperature measurements, this yields probability distributions of impurity concentrations. Acceleration with neural networks will allow real-time application on two fusion devices.