Abstract:
:Annotation of surgical video is important for establishing ground truth in surgical data science endeavors that involve computer vision. With the growth of the field over the last decade, several challenges have been identified in annotating spatial, temporal, and clinical elements of surgical video as well as challenges in selecting annotators. In reviewing current challenges, we provide suggestions on opportunities for improvement and possible next steps to enable translation of surgical data science efforts in surgical video analysis to clinical research and practice.
journal_name
Comput Assist Surg (Abingdon)journal_title
Computer assisted surgery (Abingdon, England)authors
Ward TM,Fer DM,Ban Y,Rosman G,Meireles OR,Hashimoto DAdoi
10.1080/24699322.2021.1937320keywords:
["Annotation","Image classification","Object detection","Semantic segmentation","Surgical video","inter-rater reliability","temporal annotation"]subject
Has Abstractpub_date
2021-12-01 00:00:00pages
58-68issue
1issn
2469-9322journal_volume
26pub_type
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