Determining a confidence indication for deep learning image reconstruction in computed tomography

A system for determining one or more confidence indications for machine learning image reconstruction in CT;

• wherein the system is configured to acquire energy resolved x-ray data;
• wherein the system (30;
• 40;
• 50;
• 200) is further configured to perform material-decomposition-based image reconstruction by means of machine learning image reconstruction based on the energy-resolved x-ray data including energy bin sinograms as input to generate at least one reconstructed basis image or image feature thereof;
• wherein the system is further configured to process said energy-resolved x-ray data based on at least one machine learning system to obtain a representation of a posterior probability distribution of the at least one reconstructed basis image or image feature thereof;
• wherein the system is also configured to generate one or more confidence indications for the at least one reconstructed basis image, or at least one derivative image originating from the at least one reconstructed basis image, or image feature of the at least one reconstructed basis image or the at least one derivative image, based on the representation of a posterior probability distribution;
• and
• wherein the system is configured to determine an uncertainty or confidence map of individual basis material images and also covariance between different basis material images, allowing the uncertainty or confidence map to be propagated to yield an uncertainty map for a derived image.