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The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis), but also for deeper analysis of hemodynamic functional data, such as fMRI strongly depending on the vessel structure. Such vessel geometries can be obtained by different MR angiographic. First we present algorithms for automatic vessel reconstructions from different MRA angiographic modalities. Moreover, we show that simulations using computational fluid dynamics (CFD) can be used to validate the vessel geometry, reconstructed from time-of-flight (TOF) angiograms. CFD simulations are based on phase-contrast angiography (PC-MRA) data, since these data contain rheological information (phases) besides merely amplitudes as is the case for TOF measurements. Parts of the rat brain vessel system are carefully modeled consisting of a main tube and second order branches. By analyzing velocity changes up and downstream of bifurcations, we show that CFD can be used to help detecting missing vessels in the TOF based reconstruction. We demonstrated this by artificially deleting a branch from the reconstruction and compared the flow in both resulting CFD simulations. Finally the simulations help to understand the effects of secondary branches on the flow in the main tube.