An automatic segmentation technique has been developed and applied to two renal micro-CT images. Using a 20µm voxel resolution image, the arterial and venous trees were segmented for the rat renal vasculature, distinguishing vessels down to 30µm in radius. A higher resolution 4µm voxel image of a renal vascular subtree, with vessel radial values down to 10µm, was segmented. Strahler ordering was applied to each subtree using an iterative scheme developed to integrate information from the two segmented models to reconstruct the complete topology of the entire vascular tree. An error analysis of the assigned orders quantified the robustness of the ordering process for the full model. Radial, length and connectivity data of the complete arterial and venous trees are reported by order. Substantial parallelism is observed between individual arteries and veins and the ratio of parallel vessel radii is quantified via a power law. A strong correlation with Murray's Law was established, providing convincing evidence of the "minimum work" hypothesis. Results were compared with theoretical branch angle formulations, based on the principles of "minimum shear force," were inconclusive. Three-dimensional reconstructions of renal vascular trees collected are made freely available¹ for further investigation into renal physiology and modeling studies.