Flow data resulting from steady-state simulations of blood flow in cerebral aneurysms are generally visualized by a dense and cluttered set of streamlines. The paper describes a fully automatic approach for reducing visual clutter and exposing characteristic flow structures by clustering streamlines and computing cluster representatives. While individual clustering techniques have been applied before to streamlines in 3D flow fields, a general quantitative and a domain-specific qualitative evaluation of three state-of-the-art techniques are contributed. It is shown that clustering streamlines contributes to comparing and evaluating different virtual stenting strategies. The paper is the result of a collaboration between our Visualization group (Steffen Oeltze-Jafra, Bernhard Preim), the Institute of Fluid Dynamics and Thermodynamics of our University (Gábor Janiga), the Visual Computing group (Dirk J. Lehmann, Alexander Kuhn, Holger Theisel), and the Institute of Neuroradiology of our University Hospital (Oliver Beuing). It is available here: http://dx.doi.org/10.1109/TVCG.2013.2297914. The accompanying video can be found here: http://www.youtube.com/watch?v=-RVVgqDHzdc.