TY - JOUR
T1 - SAGES consensus recommendations on an annotation framework for surgical video
AU - the SAGES Video Annotation for AI Working Groups
AU - Meireles, Ozanan R.
AU - Rosman, Guy
AU - Altieri, Maria S.
AU - Carin, Lawrence
AU - Hager, Gregory
AU - Madani, Amin
AU - Padoy, Nicolas
AU - Pugh, Carla M.
AU - Sylla, Patricia
AU - Ward, Thomas M.
AU - Hashimoto, Daniel A.
AU - Ban, Yutong
AU - Filicori, Fillipo
AU - Mascagni, Pietro
AU - Mellinger, John
AU - Schlacta, Christopher
AU - Speidel, Stefanie
AU - Juergens, Thorsten
AU - Garcia-Kilroy, Pablo
AU - Asselman, Dotan
AU - Bohnen, Jordan
AU - Draelos, Rachel Ballantyne
AU - Fuchs, Hans
AU - Henao, Ricardo
AU - Sarikaya, Duygu
AU - Boyle, Christopher
AU - Fer, Danyal
AU - Li, Zhen
AU - Ramadorai, Arvind
AU - Stoyanov, Danail
AU - Yoo, Andrew
AU - Gonzalez, Cristians
AU - Oleynikov, Dmitry
AU - Pratt, Janey
AU - Scott, Danny
AU - Vedula, Swaroop
AU - Witkowski, Elan
AU - Shimizu, Takayuki
AU - Tousignant, Mark
AU - Azagury, Dan
AU - Bridault, Flavien
AU - Dunkin, Brian
AU - Grantcharov, Teodor
AU - Jannin, Pierre
AU - Malpani, Anand
AU - Perretta, Silvana
AU - Schwaitzberg, Steven
AU - Jarc, Anthony
AU - Landfors, Kurt
AU - Mahadik, Amit
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2021/9
Y1 - 2021/9
N2 - Background: The growing interest in analysis of surgical video through machine learning has led to increased research efforts; however, common methods of annotating video data are lacking. There is a need to establish recommendations on the annotation of surgical video data to enable assessment of algorithms and multi-institutional collaboration. Methods: Four working groups were formed from a pool of participants that included clinicians, engineers, and data scientists. The working groups were focused on four themes: (1) temporal models, (2) actions and tasks, (3) tissue characteristics and general anatomy, and (4) software and data structure. A modified Delphi process was utilized to create a consensus survey based on suggested recommendations from each of the working groups. Results: After three Delphi rounds, consensus was reached on recommendations for annotation within each of these domains. A hierarchy for annotation of temporal events in surgery was established. Conclusions: While additional work remains to achieve accepted standards for video annotation in surgery, the consensus recommendations on a general framework for annotation presented here lay the foundation for standardization. This type of framework is critical to enabling diverse datasets, performance benchmarks, and collaboration.
AB - Background: The growing interest in analysis of surgical video through machine learning has led to increased research efforts; however, common methods of annotating video data are lacking. There is a need to establish recommendations on the annotation of surgical video data to enable assessment of algorithms and multi-institutional collaboration. Methods: Four working groups were formed from a pool of participants that included clinicians, engineers, and data scientists. The working groups were focused on four themes: (1) temporal models, (2) actions and tasks, (3) tissue characteristics and general anatomy, and (4) software and data structure. A modified Delphi process was utilized to create a consensus survey based on suggested recommendations from each of the working groups. Results: After three Delphi rounds, consensus was reached on recommendations for annotation within each of these domains. A hierarchy for annotation of temporal events in surgery was established. Conclusions: While additional work remains to achieve accepted standards for video annotation in surgery, the consensus recommendations on a general framework for annotation presented here lay the foundation for standardization. This type of framework is critical to enabling diverse datasets, performance benchmarks, and collaboration.
KW - Annotation
KW - Artificial intelligence
KW - Computer vision
KW - Consensus
KW - Minimally invasive surgery
KW - Surgical video
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U2 - 10.1007/s00464-021-08578-9
DO - 10.1007/s00464-021-08578-9
M3 - Article
C2 - 34231065
AN - SCOPUS:85109676129
SN - 0930-2794
VL - 35
SP - 4918
EP - 4929
JO - Surgical endoscopy
JF - Surgical endoscopy
IS - 9
ER -