Micro-computed tomography (micro-CT) provides a means for obtaining a detailed three-dimensional description of the structure of micro-vasculature in whole organs. This whole organ description allows for the examination of flow models and self similarity relationships that would otherwise be inaccessible using conventional sampling based descriptions of the micro-vasculature. The number of vessels that compose the micro-vasculature in a whole organ is so large, however, that such analysis is only feasible using automated image processing techniques. In this paper, the segmentation and data representation challenges of such analysis are examined with reference to mouse kidney vasculature. A semi-automated analysis method is described and is applied to a set of mouse kidneys to assess the feasibility and reproducibility of population studies. This analysis includes a new method to separate parallel arterial and venous vessels that are distinct but touching at the resolution of the micro-CT scan. Also described is a new formalism for representing the derived vessel structure that lends itself to regularization. Distributions of arterial and venous structural parameter are presented for six kidneys (three of each) taken from age matched animals of the GD1 strain. These results show a high degree of similarity among specimens and suggest that population studies to examine the influence of subtle disease or genetic factors are feasible.