AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design

LI, JIANNING; EHLKE, MORITZ; ESTACIO, LAURA; SHI, HAOCHEN; NEWCOMBE, VIRGINIA; ELLIS, DAVID G.; SPANEL, MICHAL; FISHMAN, ZACHARY; SHIT, SUPROSANNA; EDER, MATTHIAS; ALVES, VICTOR; PISTRACHER, KARIN; MENZE, BJOERN H.; PIMENTEL, PEDRO; LAMECKER, HANS; DOENITZ, CHRISTIAN; CHEN, XIAOJUN; FERRANTE, ENZO; AIZENBERG, MICHELE R.; HEROUT, ADAM; HARDISTY, MICHAEL R.; WANG, BOMIN; PEPE, ANTONIO; ZEFFERER, ULRIKE; SCHAFER, UTE; GLOCKER, BEN; SZENGEL, ANGELIKA; ZACHOW, STEFAN; RAMM, HEIKO; MATZKIN, FRANCO; JIN, YUAN; KODYM, OLDRICH; MAINPRIZE, JAMES G.; BAYAT, AMIRHOSSEIN; LIU, ZHI; GSAXNER, CHRISTINA; VON CAMPE, GORD; SCHMALSTIEG, DIETER; EGGER, JAN

IEEE TRANSACTION ON MEDICAL IMAGING

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Año: 2021 vol. 40 p. 2329 - 2342

0278-0062

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.