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Many analyses in neurosciences are carried out on histological and autoradiographic datasets and performed by manually drawing regions of interest on these 2D post mortem data. Such task being time-consuming, we propose an automated segmentation strategy to analyze 3D post mortem brain images. This method is based on the co-registration of a MRI-based 3D digital atlas on 3D-reconstructed post mortem data. We first deformed the original MRI on post mortem volumes. We then applied deformation parameters to warp the digital atlas. The method was tested on APP/PS1 mouse models of Alzheimer's disease and PS1 control littermates. Its reliability was qualitatively evaluated and a quantitative assessment was performed by comparing atlas and manual segmentations. Our results show this approach is promising to investigate at organ scale post mortem mouse datasets faster and in a more robust manner than with classical methods.