Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive Manufacturing

Object-space model optimization (OSMO) has been proven to be a simple and high-accuracy approach for additive manufacturing of tomographic reconstructions compared with other approaches. In this paper, an improved OSMO algorithm is proposed in the context OSMO. addition two steps each iteration OSMO, another are introduced: one step enhances target regions’ in-part edges intermediate model, weakens out-of-part further improve reconstruction accuracy boundary. Accordingly, new quality metric volumetric printing, named ‘Edge Error’, defined. Finally, on diverse exemplary geometries show that all metrics, such as VER, PW, IPDR, Edge Error, significantly improved; thus, achieves better performance convergence