Back to Search
Start Over
SAGES consensus recommendations on an annotation framework for surgical video
- Source :
- Surgical Endoscopy; September 2021, Vol. 35 Issue: 9 p4918-4929, 12p
- Publication Year :
- 2021
-
Abstract
- 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.
Details
- Language :
- English
- ISSN :
- 09302794 and 14322218
- Volume :
- 35
- Issue :
- 9
- Database :
- Supplemental Index
- Journal :
- Surgical Endoscopy
- Publication Type :
- Periodical
- Accession number :
- ejs57018117
- Full Text :
- https://doi.org/10.1007/s00464-021-08578-9