Challenges in surgical video annotation. Issue 1 (1st January 2021)

• Record Type: Journal Article
• Authors: Ward, Thomas M.; Fer, Danyal M.; Ban, Yutong; Rosman, Guy; Meireles, Ozanan R.; Hashimoto, Daniel A.
• Is Part Of: Computer assisted surgery. Volume 26:Issue 1(2021)
• Page Start: 58
• Page End: 68
• Publication Date: 2021-01-01
• Subjects: Surgical video -- Annotation -- Image classification -- Object detection -- Semantic segmentation -- temporal annotation -- inter-rater reliability; Computer-assisted surgery -- Periodicals
• DOI: 10.1080/24699322.2021.1937320
• Languages: English
• ISSNs: 2469-9322

Abstract

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.