A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the
potential for many fields—including medicine—to benefit from the insights that AI techniques …

Objective: To provide an overview of ML models and data streams utilized for automated
surgical phase recognition. Background: Phase recognition identifies different steps and …

The fields of computer vision (CV) and artificial intelligence (AI) have undergone rapid
advancements in the past decade, many of which have been applied to the analysis of …

Automatic surgical phase recognition is a challenging and crucial task with the potential to
improve patient safety and become an integral part of intra-operative decision-support …

Surgical tool presence detection and surgical phase recognition are two fundamental yet
challenging tasks in surgical video analysis as well as very essential components in various …

In this paper we introduce OperA, a transformer-based model that accurately predicts
surgical phases from long video sequences. A novel attention regularization loss …

Real-time surgical phase recognition is a fundamental task in modern operating rooms.
Previous works tackle this task relying on architectures arranged in spatio-temporal order …

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 …

Technology has advanced surgery, especially minimally invasive surgery (MIS), including
laparoscopic surgery and robotic surgery. It has led to an increase in the number of …

Background Automatic surgical workflow recognition is a key component for developing the
context-aware computer-assisted surgery (CA-CAS) systems. However, automatic surgical …