Uncertainty in bedload estimates for gravel bed rivers is largely driven by our inability to characterize arrangement, orientation and resultant forces of fluvial sediment in river beds. Water working of grains leads to structural differences between areas of the bed through particle sorting, packing, imbrication, mortaring and degree of bed armoring. In this study, non-destructive, micro-focus X-ray computed tomography (CT) imaging in 3D is used to visualize, quantify and assess the internal geometry of sections of a flume bed that have been extracted keeping their fabric intact. Flume experiments were conducted at 1:1 scaling of our prototype river. Here we present some image processing and derived metrics from a CT scanned sample from our flume experiments. This is the first time bed stability has been studied in 3D using CT scanned images of sediment from the bed surface to depths well into the subsurface. The derived metrics and inter-granular relationships and characterization of bed structures will lead to improved bedload estimates with reduced uncertainty.