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
; 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 
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 ...
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