The image quality of unenhanced magnetic resonance angiography, which images blood vessels without contrast agents, is limited by constraints related to scan time. To address this problem, techniques that undersample angiographic data and then apply regularized reconstructions are used. Conventional reconstructions employ regularization terms with uniform spatial weighting. Thus, they can yield improper suppression of aliasing artifacts and poor blood/background contrast. In this study, a reconstruction strategy is evaluated that applies spatially-adaptive regularization based on vessel maps obtained via a tractographic segmentation. This strategy is compared with conventional methods in terms of peak signal to noise ratio, structural similarity and contrast.