SAGES consensus recommendations on an annotation framework for surgical video
SAGES consensus recommendations on an annotation framework for surgical video
About this item
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Author / Creator
Publisher
New York: Springer US
Journal title
Language
English
Formats
Publication information
Publisher
New York: Springer US
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Scope and Contents
Contents
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....
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Full title
SAGES consensus recommendations on an annotation framework for surgical video
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Record Identifier
TN_cdi_hal_primary_oai_HAL_hal_03513622v1
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_hal_primary_oai_HAL_hal_03513622v1
Other Identifiers
ISSN
0930-2794
E-ISSN
1432-2218
DOI
10.1007/s00464-021-08578-9
