Deep brain stimulation (DBS) is a treatment for several neurological disorders including Parkinson's disease, essential tremor, and epilepsy. The neurosurgical procedure involves implanting a lead of electrodes to a deep brain target and thereafter electrically stimulating that target to suppress symptoms. To reduce the probability of intracranial bleeding during implantation, neurosurgeons carefully plan out a patient-specific lead trajectory that avoids passing the lead through regions with major blood vessels. This process can be tedious, and there is a need to provide neurosurgeons with a more efficient and quantitative means to identify major blood vessels on a patient-specific basis. Here, we developed a modular graphical user interface (GUI) containing anatomically segmented digital reconstructions of patient vasculature, cortex, and deep brain target anatomy from preoperative high-field (3T and 7T) MRI. The system prompts users to identify the deep brain target, and then algorithmically calculates a log-scale blood vessel density along the length of potential lead trajectories that pivot around the deep brain target. Heatmaps highlighting regions with low blood vessel density were calculated for cortical and subcortical vasculature models. The modeling framework enabled users to further interact with the models by panning, rotating, zooming, showing, or hiding the various anatomical reconstructions and heatmaps. Providing surgeons with quantitative, patient specific vasculature data has the potential to further reduce the likelihood of hemorrhage events during microelectrode mapping and DBS lead implantation.