Recent developments in the field of structural MRI (sMRI) have yielded several imaging routines that allow to detect fibre orientations and myelin content (e.g. diffusion tensor imaging (DTI), wT1/wT2 and magnetisation transfer) at details of sub-mm resolution. However, this resolution is an order of magnitude coarser than what would be required to image the network buildings blocks (e.g. neuronal columns). More importantly current sMRI spatial resolution is too coarse to detect neurodegenerative processes at the early stages. Histological methods used for validating sMRI benefited greatly from recent developments towards “3D Histology” by applying clearing steps that allow to image immunohistochemically-stained ex-vivo organs without the need for sectioning the tissue. 3D histology at the micrometre resolution will generate large data sets of up to 1 Terabyte per brain and will require the implementation of novel computational approaches (mosaics, parallel computing) that can make use of the HPC2N-computational cluster at Umea University.