The architecture of the supplying brain blood vessels is believed to impact the occurrence and severity of common cerebrovascular diseases such as ischemic strokes or intracranial aneurysms. In this project, we study methods to efficiently quantify the variability in human cerebral vasculature and how this variability is linked to cerebrovascular pathologies. We employ geometric and graph-based models of the vasculature to analyze and profile the cerebral angioarchitecture in large patient cohorts. The range of methods to use includes medical image analysis, machine learning, medical statistics and quantitative morphology.