CATARACTS: Challenge on automatic tool annotation for cataRACT surgery

•The challenge on automatic tool annotation for cataract surgery is presented.•Tool usage was manually annotated for 21 tools in 50 cataract surgery videos.•Various deep learning solutions were proposed by 14 teams.•Lessons learnt from the differential analysis of these solutions are presented.•Auto...

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Veröffentlicht in:	Medical image analysis Jg. 52; S. 24 - 41
Hauptverfasser:	Al Hajj, Hassan, Lamard, Mathieu, Conze, Pierre-Henri, Roychowdhury, Soumali, Hu, Xiaowei, Maršalkaitė, Gabija, Zisimopoulos, Odysseas, Dedmari, Muneer Ahmad, Zhao, Fenqiang, Prellberg, Jonas, Sahu, Manish, Galdran, Adrian, Araújo, Teresa, Vo, Duc My, Panda, Chandan, Dahiya, Navdeep, Kondo, Satoshi, Bian, Zhengbing, Vahdat, Arash, Bialopetravičius, Jonas, Flouty, Evangello, Qiu, Chenhui, Dill, Sabrina, Mukhopadhyay, Anirban, Costa, Pedro, Aresta, Guilherme, Ramamurthy, Senthil, Lee, Sang-Woong, Campilho, Aurélio, Zachow, Stefan, Xia, Shunren, Conjeti, Sailesh, Stoyanov, Danail, Armaitis, Jogundas, Heng, Pheng-Ann, Macready, William G., Cochener, Béatrice, Quellec, Gwenolé
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.02.2019 Elsevier BV Elsevier
Schlagworte:	Algorithms Annotations Cataract Extraction - instrumentation Cataract surgery Cataracts Challenge Computer Science Deep Learning Eye surgery Humans Image analysis Image detection Image processing Laparoscopy Machine learning Medical Imaging Motivation Surgery Surgical Instruments Video analysis Workflow Deep learning Cataract surgery Video analysis Challenge
ISSN:	1361-8415, 1361-8423, 1361-8423
Online-Zugang:	Volltext
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