Electrical stimulation of the deep parts of the brain is the standard answer for patients subject to drug-refractory movement disorders. Collective analysis of data collected during surgeries are crucial in order to provide more systematic planning assistance and understanding the physiological mechanisms of action. To that end, the process of normalizing anatomies captured with Magnetic Resonance imaging across patients is a key component. In this work, we present the optimization of a workflow designed to create group specific anatomical templates: a group template is refined iteratively using the results of successive non-linear image registrations. I norder to improve the results in the basal-ganglia area, the process is refined in this specific volume of interest. All non-linear registrations were executed using the Advanced Normalization Tools (ANTs). The quality of the normalization was measured using the manual delineation of anatomical structures produced during the planning of the surgery and their spacial overlap after trans- formation in the template space by means of Dice coefficient and mean surface distance. The parameters of the workflow evaluated were: the use of multiple modalities sequentially or together during each registration to the template, the number of iterations in the template creation and the fine settings of the non-linear registration tool. Using the T1 and white matter attenuated inverse recovery modalities together produced the best results, especially in the center of the brain. The optimal numbers of iterations of the template creation were higher than those advised in the literature and our previous works. Finally, the setting of the nonlinear registration tool that improved results the most was the activation of the registrationwith the native voxel sizes of images, as opposed to down-sampled version of the images. Theuse of the delineation of the anatomical structures as a mean to measure the quality of the anatomical template of a group of patient allowed to optimize the normalization process and obtain the best possible anatomical normalization of this specific group of patient. The most crucial points were the combination of multiple modalities in order to maximize the quality of information available during image registration and the activation of the registration with native voxel size. The anatomical template of the group will be used to summarize and analyze peri-operative measurements during test stimulation. The aim is that the conclusions obtained from this analysis will be useful for assistance during the planning of new surgeries.