Challenges in surgical video annotation

• Main Authors: Thomas M. Ward, Danyal M. Fer, Yutong Ban, Guy Rosman, Ozanan R. Meireles, Daniel A. Hashimoto
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2021-01-01
• Series: Computer Assisted Surgery
• Subjects: surgical video; annotation; image classification; object detection; semantic segmentation; temporal annotation; inter-rater reliability
• Online Access: http://dx.doi.org/10.1080/24699322.2021.1937320

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.