Cholec80-CVS: An open dataset with an evaluation of Strasberg’s critical view of safety for AI
Manuel Ríos, María Alejandra Molina-Rodríguez, Daniella Londoño, Camilo Andrés Guillén, Sebastián Sierra, Felipe Zapata-Uribe, Luis Felipe Giraldo
Abstract
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.