Cholec80-CVS: An open dataset with an evaluation of Strasberg's critical view of safety for Artificial Intelligence

Strasberg's criteria to detect a critical view of safety is a widely known strategy to reduce bile duct injuries during laparoscopic cholecystectomy. In spite of its popularity and efficiency, recent studies have shown that human miss-identification errors have led to important bile duct injuries occurrence rates. Developing tools based on artificial intelligence that facilitate the identification of a critical view of safety in cholecystectomy surgeries can potentially minimize the risk of such injuries. With this goal in mind, we present Cholec80-CVS, the first open dataset with video annotations of Strasberg's Critical View of Safety (CVS) criteria. Our dataset contains CVS criteria annotations provided by skilled surgeons for all videos in the well-known Cholec80 open video dataset. We consider that Cholec80-CVS is the first step towards the creation of intelligent systems that can assist humans during laparoscopic cholecystectomy.斯特拉斯伯格安全视野（Critical View of Safety, CVS）识别标准是腹腔镜胆囊切除术术中降低胆管损伤的经典策略。尽管该标准应用广泛且效果优异，但近期研究显示，人为识别失误仍导致了较高的胆管损伤发生率。开发基于人工智能的工具以辅助胆囊切除术术中安全视野的识别，有望大幅降低此类损伤的风险。基于此目标，我们构建了Cholec80-CVS数据集——首个针对斯特拉斯伯格安全视野（CVS）标准的带视频标注的开源数据集。该数据集针对知名开源视频数据集Cholec80中的全部手术视频，提供了由资深外科医师标注的CVS标准相关标注信息。我们认为，Cholec80-CVS是开发可在腹腔镜胆囊切除术术中为医师提供辅助的智能系统的第一步。