SURGIVID: Annotation-Efficient Surgical Video Object Discovery

Understand

Surgical scenes convey crucial information about the quality of surgery.

• Pixel-wise localization of tools and anatomical structures is the first task towards deeper surgical analysis for microscopic or endoscopic surgical views.
• This is typically done via fully-supervised methods which are annotation greedy and in several cases, demanding medical expertise.
• Considering the profusion of surgical videos obtained through standardized surgical workflows, we propose an annotation-efficient framework for the semantic segmentation of surgical scenes.