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Whole brain neuroanatomy using tera-voxel light-microscopic data sets is ofmuch current interest. A fundamental problem in this field is the mapping ofindividual brain data sets to a reference space. Previous work has notrigorously quantified the distortions in brain geometry from in-vivo to ex-vivobrains due to the tissue processing, which will be important when computingproperties such as local cell and process densities at the voxel level increating reference brain maps. Further, existing approaches focus onregistering uni-modal volumetric data; however, given the increasing interestin the marmoset model for neuroscience research, it is necessary tocross-register multi-modal data sets including MRIs and multiple histologicalseries that can help address individual variations in brain architecture. Herewe present a computational approach for same-subject multimodal MRI guidedreconstruction of a histological series, jointly with diffeomorphic mapping toa reference atlas. We quantify the scale change during the different stages ofhistological processing of the brains using the Jacobian determinant of thediffeomorphic transformations involved. There are two major steps in thehistology process with associated scale distortions (a) brain perfusion (b)histological sectioning and reassembly. By mapping the final image stacks tothe ex-vivo post fixation MRI, we show that tape-transfer histology can bereassembled accurately into 3D volumes with a local scale change of 2.0 $\pm$0.4% per axis dimension. In contrast, the perfusion step, as assessed bymapping the in-vivo MRIs to the ex-vivo post fixation MRIs, shows a largerlocal scale change of 6.9 $\pm$ 2.1% per axis dimension. This is the firstsystematic quantification of the local metric distortions associated withwhole-brain histological processing, and we expect that the results willgeneralize to other species.

Multimodal Cross-registration and Quantification of Metric Distortions in Whole Brain Histology of Marmoset using Diffeomorphic Mappings