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https://hdl.handle.net/1822/78123| Título: | AutoImplant 2020 - First MICCAI Challenge on Automatic Cranial Implant Design |
| Autor(es): | Li, Jianning Pimentel, Pedro Szengel, Angelika Ehlke, Moritz Lamecker, Hans Zachow, Stefan Estacio, Laura Doenitz, Christian Ramm, Heiko Shi, Haochen Chen, Xiaojun Matzkin, Franco Newcombe, Virginia Ferrante, Enzo Jin, Yuan Ellis, David G. Aizenberg, Michele R. Kodym, Oldrich Spanel, Michal Herout, Adam Mainprize, James G. Fishman, Zachary Hardisty, Michael R. Bayat, Amirhossein Shit, Suprosanna Wang, Bomin Liu, Zhi Eder, Matthias Pepe, Antonio Gsaxner, Christina Alves, Victor Zefferer, Ulrike Von Campe, Gord Pistracher, Karin Schafer, Ute Schmalstieg, Dieter Menze, Bjoern H. Glocker, Ben Egger, Jan |
| Palavras-chave: | cranioplasty deep learning shape inpainting shape prior skull reconstruction statistical shape model Volumetric shape completion Skull Shape Implants Three-dimensional displays Cranial Image reconstruction Biomedical imaging |
| Data: | 2021 |
| Editora: | IEEE |
| Revista: | IEEE Transactions on Medical Imaging |
| Citação: | Li, J., Pimentel, P., Szengel, A., Ehlke, M., Lamecker, H., Zachow, S., … Egger, J. (2021, September). AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design. IEEE Transactions on Medical Imaging. Institute of Electrical and Electronics Engineers (IEEE). http://doi.org/10.1109/tmi.2021.3077047 |
| Resumo(s): | The aim of this paper is to provide a comprehensive overview of the MICCAI 2020 AutoImplant Challenge. The approaches and publications submitted and accepted within the challenge will be summarized and reported, highlighting common algorithmic trends and algorithmic diversity. Furthermore, the evaluation results will be presented, compared and discussed in regard to the challenge aim: seeking for low cost, fast and fully automated solutions for cranial implant design. Based on feedback from collaborating neurosurgeons, this paper concludes by stating open issues and post-challenge requirements for intra-operative use. The codes can be found at https://github.com/Jianningli/tmi. |
| Tipo: | Artigo |
| URI: | https://hdl.handle.net/1822/78123 |
| DOI: | 10.1109/TMI.2021.3077047 |
| ISSN: | 0278-0062 |
| Versão da editora: | https://ieeexplore.ieee.org/document/9420655 |
| Arbitragem científica: | yes |
| Acesso: | Acesso restrito UMinho |
| Aparece nas coleções: |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| 09420655.pdf Acesso restrito! | 4,52 MB | Adobe PDF | Ver/Abrir |
