To obtain an accurate representation of a brain structural connectivity, diffusion MRI and fiber tracking depend on a good understanding of white matter fiber structures. Although the tracking methods work well when performed in single orientation fiber bundles, most methods are limited in more complex cases, especially to take into account crossing, fanning, and kissing fibers. A recent international fiber tracking challenge concluded that most tracking algorithms generated 4-5 times more false positive tracks than true tracks on average. This was attributed in large part to a lack of knowledge about the fiber crossing geometry. There is thus a dire need to study more complex fiber geometries to improve the tractography algorithms, for example by classifying those geometries into characteristic crossing topologies (e.g., fanning, curving, bottleneck, pure crossing, ...). Here, we propose a multimodal neuroimaging pipeline to identify and acquire fiber crossing areas in whole mouse brains. Our method uses the Allen Mouse Brain connectivity atlas and tractogram analysis using diffusion MRI techniques to identify candidate regions of interests containing fiber crossings based on two predetermined retrograde viral injection site locations. Based on serial OCT acquisitions, we confirmed the location of crossings. Further experiments will validate in detail the structural nature of crossings using retrograde injections of fluorescent tracers and whole mouse brain serial blockface histology. We believe that this new methodological approach will provide indispensable data for the development of a new generation of tractography algorithms that better resolve complex fiber geometries.