Multicentric exploration of tool annotation in robotic surgery: lessons learned when starting a surgical artificial intelligence project.
Journal:
Surgical endoscopy
Published Date:
Aug 8, 2022
Abstract
BACKGROUND: Artificial intelligence (AI) holds tremendous potential to reduce surgical risks and improve surgical assessment. Machine learning, a subfield of AI, can be used to analyze surgical video and imaging data. Manual annotations provide veracity about the desired target features. Yet, methodological annotation explorations are limited to date. Here, we provide an exploratory analysis of the requirements and methods of instrument annotation in a multi-institutional team from two specialized AI centers and compile our lessons learned.