Brain morphometric mapping in genetically modified mouse lines may permit to relate genetic mutations to clinically relevant endophenotypes without the complexity of genetic heterogeneity and the uncontrolled impact of gene-gene and gene-environment interactions typical of human populations¹. However, substantial differences in the anatomical organisation of human and rodent brain prevent a straightforward extension of clinical neuroimaging tools to mouse brain imaging and most published studies lack a detailed description of the complex workflow required to process, analyse and quantify structural MRI alterations. To address these issues, here we provide a detailed methodological description of our semi-automated operational workflow for voxel based morphometry, cortical thickness estimation and automated anatomical mapping of the mouse brain. To show the capabilities of our methods based on the ANTs toolkit², we describe its application to quantify morphological alterations in socially-impaired BTBR T+Itpr3tf/J mice with respect to normo social C57BL/6J controls^3-4.Preprocessing. An automatic registration-based approach has been devised to automate skull-stripping and avoid error-prone manual segmentation, and two independent bias corrections are executed to correct for intensity non-uniformity within the same tissue type (Fig.1). An iterative five step multi-scale alignment process is performed using diffeomorphic registration to construct a study based template from skull stripped and bias corrected wild type mice and establish a common reference space for all the subsequent analyses. Automated anatomical labelling. Registration based labelling is performed to assess volumetric anatomical differences in gross morphology and relies on non-linear registrations of two labelled neuroanatomical reference MRI atlas via the study based template. Cortical thickness. A diffeomorphic registration based cortical thickness measure is used to establish a continuous one-to-one correspondence between the inner and outer cortical surfaces and estimate a voxelwise distance between the two interfaces. VBM. Individual images are registered to the study based template and segmented to calculate tissue probability maps (Fig.2). The separation of the different tissues is improved by initializing the process with the probability maps of the study based template previously segmented. The Jacobian determinants of the deformation field were extracted and applied to modulate the grey matter probability maps calculated during the segmentation. This expedient permits the analysis of grey matter probability maps in terms of local volumetric variation instead of tissue density. The resulting modulated grey matter probability maps were then smoothed using a Gaussian kernel with a sigma of three voxel width. Statistics. Standard non-parametric Monte Carlo test with 5000 random permutations was performed coupled with threshold-free cluster enhancement and multiple comparisons correction using a cluster-based threshold of 0.01.Cross-strain volumetric analysis highlighted the presence of a general reduction in cortical and subcortical volume in BTBR mice with respect to controls. Further voxelwise investigations using whole-brain VBM revealed widespread and bilateral reductions in GM volume across dorsofrontal, cingulate, retrosplenial, occipital and parietal cortex in BTBR (Fig.3). In good agreement with the results of automated anatomical labelling and VBM mapping, a widespread reduction in mean cortical thickness was observed in BTBR mice (Fig.4). Importantly, manual measurements of exemplificative regions were highly correlated with cortical thickness estimates (Fig.5).The vast majority of current morphometric studies on the mouse brain lacks a detailed description of the complex workflow required to process and analyse different readouts. We provide a detailed description of methods to quantify morphoanatomical alterations in socially-impaired BTBR mice. We show that these approaches can reliably detect both focal and large scale gray matter alterations using complementary readouts. Importantly, our VBM workflow can be straightforwardly extended to perform tensor based morphometry, where Jacobian maps can be used to localise inter-group differences in the local volumes of brain structures at the voxel level. Morphological alterations comparable to those we mapped have been recently described in BTBR mice by others⁵, thus permitting an empirical cross-laboratory validation of our findings.The use of complementary semi-automated MRI morphometric measurers can help to pinpoint the pathological bases of brain morphometric changes of neuropathological origin. The detailed operational workflow of the present work is expected to help the implementation of fine-grained morphoanatomical mapping methods by non-expert users, promote future comparative study, and, above all, facilitate forward and back translation of MRI preclinical and clinical research findings.