We acquired diffusion-weighted and CEST data of the brain of 38 healthy volunteers. A MPRAGE and SWI based segmentation into 102 brain regions revealed unique diffusion and chemical MR signals on average. More importantly, we could infer these tissue classes form individual voxel data using a neural network. The revival of this old paradigm for tissue characterization from the 1990s points to the fact that unique MR signals of different brain regions exist and can be used to determine the tissue type voxel-wise. The approach as such is general and could unify the ever-growing diversity of MR contrasts.