Simultaneous PET–MR acquisition reduces the possibility of registration mismatch between the two modalities. This facilitates the application of techniques, either during reconstruction or post-reconstruction, that aim to improve the PET resolution by utilising structural information provided by MR. However, in order to validate such methods for brain PET–MR studies it is desirable to evaluate the performance using data where the ground truth is known. In this work, we present a framework for the production of datasets where simulations of both the PET and MR, based on real data, are generated such that reconstruction and post-reconstruction approaches can be fairly compared. •A framework for simulating realistic brain PET–MR images is proposed.•The imaging data created is formed from real acquisitions.•Partial volume correction techniques can be fairly compared using this framework.