Purpose: To present and evaluate the feasibility of a novel automatic method for generating 4D blood flow visualizations fusing high spatial resolution 3D and time-resolved (4D) magnetic resonance angiography (MRA) datasets. Materials and Methods: In a first step, the cerebrovascular system is segmented in the 3D MRA dataset and a surface model is computed. The hemodynamic information is extracted from the 4D MRA dataset and transferred to the surface model using rigid registration where it can be visualized color-coded or dynamically over time. The presented method was evaluated using software phantoms and 20 clinical datasets from patients with an arteriovenous malformation. Clinical evaluation was performed by comparison of Spetzler-Martin scores determined from the 4D blood flow visualizations and corresponding digital subtraction angiographies. Results: The performed software phantom validation showed that the presented method is capable of producing reliable visualization results for vessels with a minimum diameter of 2 mm for which a mean temporal error of 0.27 seconds was achieved. The clinical evaluation based on 20 datasets comparing the 4D visualization to DSA images revealed an excellent interrater reliability. Conclusion: The presented method enables an improved combined representation of blood flow and anatomy while reducing the time needed for clinical rating.