학술논문
AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design
Document Type
Periodical
Author
Li, J.; Pimentel, P.; Szengel, A.; Ehlke, M.; Lamecker, H.; Zachow, S.; Estacio, L.; Doenitz, C.; Ramm, H.; Shi, H.; Chen, X.; Matzkin, F.; Newcombe, V.; Ferrante, E.; Jin, Y.; Ellis, D.G.; Aizenberg, M.R.; Kodym, O.; Spanel, M.; Herout, A.; Mainprize, J.G.; Fishman, Z.; Hardisty, M.R.; Bayat, A.; Shit, S.; Wang, B.; Liu, Z.; Eder, M.; Pepe, A.; Gsaxner, C.; Alves, V.; Zefferer, U.; von Campe, G.; Pistracher, K.; Schafer, U.; Schmalstieg, D.; Menze, B.H.; Glocker, B.; Egger, J.
Source
IEEE Transactions on Medical Imaging IEEE Trans. Med. Imaging Medical Imaging, IEEE Transactions on. 40(9):2329-2342 Sep, 2021
Subject
Language
ISSN
0278-0062
1558-254X
1558-254X
Abstract
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.