Hemodynamic and mechanical factors of the vascular system are assumed to play a major role in understanding, e.g., initiation, growth and rupture of cerebral aneurysms. Among those factors, cardiac cycle-related pulsatile motion and deformation of cerebral vessels currently attract much interest. However, imaging of those effects requires high spatial and temporal resolution and remains challenging - and similarly does the analysis of the acquired images: Flow velocity changes and contrast media inflow cause vessel intensity variations in related temporally resolved computed tomography and magnetic resonance angiography data over the cardiac cycle and impede application of intensity threshold-based segmentation and subsequent motion analysis. In this work, a flow phantom for generation of ground-truth images for evaluation of appropriate segmentation and motion analysis algorithms is developed. The acquired ground-truth data is used to illustrate the interplay between intensity fluctuations and (erroneous) motion quantification by standard threshold-based segmentation, and an adaptive threshold-based segmentation approach is proposed that alleviates respective issues. The results of the phantom study are further demonstrated to be transferable to patient data.