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 of OSMO. In addition to the two model optimi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Micromachines |
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| Online Access: | https://www.mdpi.com/2072-666X/14/7/1362 |
| _version_ | 1797588152862375936 |
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| author | Yanchao Zhang Minzhe Liu Hua Liu Ce Gao Zhongqing Jia Ruizhan Zhai |
| author_facet | Yanchao Zhang Minzhe Liu Hua Liu Ce Gao Zhongqing Jia Ruizhan Zhai |
| author_sort | Yanchao Zhang |
| collection | DOAJ |
| description | 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 of OSMO. In addition to the two model optimization steps in each iteration of OSMO, another two steps are introduced: one step enhances the target regions’ in-part edges of the intermediate model, and the other step weakens the target regions’ out-of-part edges of the intermediate model to further improve the reconstruction accuracy of the target boundary. Accordingly, a new quality metric for volumetric printing, named ‘Edge Error’, is defined. Finally, reconstructions on diverse exemplary geometries show that all the quality metrics, such as VER, PW, IPDR, and Edge Error, of the new algorithm are significantly improved; thus, this improved OSMO approach achieves better performance in convergence and accuracy compared with OSMO. |
| first_indexed | 2024-03-11T00:49:44Z |
| format | Article |
| id | doaj.art-51a89bf1584d4a13abdd33d9cb5772bf |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-03-11T00:49:44Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-51a89bf1584d4a13abdd33d9cb5772bf2023-11-18T20:32:21ZengMDPI AGMicromachines2072-666X2023-06-01147136210.3390/mi14071362Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive ManufacturingYanchao Zhang0Minzhe Liu1Hua Liu2Ce Gao3Zhongqing Jia4Ruizhan Zhai5Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (CAS), Changchun 130033, ChinaLaser Institute, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266000, ChinaCenter for Advanced Optoelectronic Functional Materials Research, and Key Laboratory for UV Emitting Materials and Technology of Ministry of Education, National Demonstration Center for Experimental Physics Education, Northeast Normal University, Changchun 130024, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (CAS), Changchun 130033, ChinaLaser Institute, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266000, ChinaLaser Institute, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266000, ChinaObject-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 of OSMO. In addition to the two model optimization steps in each iteration of OSMO, another two steps are introduced: one step enhances the target regions’ in-part edges of the intermediate model, and the other step weakens the target regions’ out-of-part edges of the intermediate model to further improve the reconstruction accuracy of the target boundary. Accordingly, a new quality metric for volumetric printing, named ‘Edge Error’, is defined. Finally, reconstructions on diverse exemplary geometries show that all the quality metrics, such as VER, PW, IPDR, and Edge Error, of the new algorithm are significantly improved; thus, this improved OSMO approach achieves better performance in convergence and accuracy compared with OSMO.https://www.mdpi.com/2072-666X/14/7/1362volumetric additive manufacturingtomographic reconstructionoptimizationOSMOedge enhanced |
| spellingShingle | Yanchao Zhang Minzhe Liu Hua Liu Ce Gao Zhongqing Jia Ruizhan Zhai Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive Manufacturing Micromachines volumetric additive manufacturing tomographic reconstruction optimization OSMO edge enhanced |
| title | Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive Manufacturing |
| title_full | Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive Manufacturing |
| title_fullStr | Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive Manufacturing |
| title_full_unstemmed | Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive Manufacturing |
| title_short | Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive Manufacturing |
| title_sort | edge enhanced object space model optimization of tomographic reconstructions for additive manufacturing |
| topic | volumetric additive manufacturing tomographic reconstruction optimization OSMO edge enhanced |
| url | https://www.mdpi.com/2072-666X/14/7/1362 |
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