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Surface roughness is traditionally evaluated with contact profilometry; however, these methods are not compatible with complex additive manufactured lattice structures due to limited physical access. For these scenarios, computed tomography (CT) is often used to provide qualitative insight into surface roughness but does not directly yield roughness profile data. This research describes a hybrid approach for the non-destructive quantification of roughness profile data for lattice structures based on the mathematical reconstruction and interpretation of CT data. Formal analyses are applied to propose the theoretical minimum CT voxel size required to characterise surface roughness for a specified sampling length. The method is verified against optical data for nominally flat metallic specimens and applied to metallic and polymeric cylinders fabricated by powder bed fusion and material extrusion respectively. This research also assesses the influence of CT reconstruction thresholding as a process variable and finds that roughness profile data is only weakly influenced by thresholding settings, due to scattering effects at the surface — a novel finding that provides certainty for the industrial application of this method. The ability of the proposed method to accurately characterise the inherent surface roughness of these processes as well as the effect of specimen orientation is thus demonstrated, enabling full geometric characterisation supporting subsequent certification analysis. The method can be algorithmically implemented in combination with the generative design of complex lattice structures to support structural certification requirements.