Mouse brain atlases based on histology can be improved through the reconstruction of the 2D histological sections into a continuous 3D volume. Impediments to a continuous reconstruction include distortion caused by excision, fixation, and sectioning of the brain. In prior works, MR images have been used as a reference for global alignment of the sections and various methods have been implemented for local alignment. In this thesis, we offered an alternative method for local alignment and developed a method for registering orthogonal histological data sets into one coordinate system. As an end result we established a comprehensive mouse brain atlas with Nissl-stained histology images with 362 coronal, 162 horizontal, and 112 sagittal histological sections at 40 Β΅m interval. For the global alignment, our MRI/CT population atlas was used to guide the alignment accuracy. The local alignment was performed using Large Deformation Diffeomorphic Metric Mapping (LDDMM) with a hierarchical approach to minimize structural discontinuity. Then the coordinate consistency was optimized by iteratively registering the three 3D volume data from the coronal, horizontal, and sagittal sections. The landmark-based analysis revealed the MRI-histology accuracy level was 0.1632 Β± 0.1131 mm. This work established the coordinate link between the MRI/CT atlas and around 300 GB of histology data in the cellular-level anatomical information
