Abstract The Segment Anything Model (SAM) is the first foundation model for general image
segmentation. It has achieved impressive results on various natural image segmentation …

Surgical scene perception via videos is critical for advancing robotic surgery, telesurgery,
and AI-assisted surgery, particularly in ophthalmology. However, the scarcity of diverse and …

In the field of computer-and robot-assisted minimally invasive surgery, enormous progress
has been made in recent years based on the recognition of surgical instruments in …

This paper introduces SKiT, a fast Key information Transformer for phase recognition of
videos. Unlike previous methods that rely on complex models to capture long-term temporal …

Online surgical phase recognition plays a significant role towards building contextual tools
that could quantify performance and oversee the execution of surgical workflows. Current …

Formalizing surgical activities as triplets of the used instruments, actions performed, and
target anatomies is becoming a gold standard approach for surgical activity modeling. The …

Surgical data science is devoted to enhancing the quality, safety, and efficacy of
interventional healthcare. While the use of powerful machine learning algorithms is …

Natural language could play an important role in developing generalist surgical models by
providing a broad source of supervision from raw texts. This flexible form of supervision can …

Existing state-of-the-art methods for surgical phase recognition either rely on the extraction
of spatial-temporal features at a short-range temporal resolution or adopt the sequential …

Automated laparoscope field of view (FoV) control in minimal invasive surgery (MIS) poses
challenges, as existing solutions failed to address dynamic surgical FoV requirements …