The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Transformers have dominated the field of natural language processing and have recently
made an impact in the area of computer vision. In the field of medical image analysis …

The intraoperative activity of a surgeon has substantial impact on postoperative outcomes.
However, for most surgical procedures, the details of intraoperative surgical actions, which …

Out of all existing frameworks for surgical workflow analysis in endoscopic videos, action
triplet recognition stands out as the only one aiming to provide truly fine-grained and …

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 …

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 …

Surgery digitalization is the process of creating a virtual replica of real-world surgery also
referred to as a surgical digital twin (SDT). It has significant applications in various fields …

Most benchmarks for studying surgical interventions focus on a specific challenge instead of
leveraging the intrinsic complementarity among different tasks. In this work, we present a …

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

Objective: In the last two decades, there has been a growing interest in exploring surgical
procedures with statistical models to analyze operations at different semantic levels. This …