Modern endoscopy relies on digital technology, from high-resolution imaging sensors and
displays to electronics connecting configurable illumination and actuation systems for …

Studies show lots of advanced research on various data types such as image, speech, and
text using deep learning techniques, but nowadays, research on video processing is also an …

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 …

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 …

Automatic surgical workflow recognition is a key component for developing context-aware
computer-assisted systems in the operating theatre. Previous works either jointly modeled …

Recognition of surgical activity is an essential component to develop context-aware decision
support for the operating room. In this work, we tackle the recognition of fine-grained …

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 …

Minimally invasive surgical instrument visual detection and tracking is one of the core
algorithms of minimally invasive surgical robots. With the development of machine vision …