Recent developments in data science in general and machine learning in particular have
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …

Telesurgical robotics, as a technical solution for robot-assisted minimally invasive surgery
(RAMIS), has become the first domain within medicosurgical robotics that achieved a true …

Three-dimensional reconstruction of images acquired through endoscopes is playing a vital
role in an increasing number of medical applications. Endoscopes used in the clinic are …

Surgical simulators not only allow planning and training of complex procedures, but also
offer the ability to generate structured data for algorithm development, which may be applied …

The previous image synthesis research for surgical vision had limited results for real-world
applications with simple simulators, including only a few organs and surgical tools and …

Surgical instrument segmentation can be used in a range of computer assisted interventions
and automation in surgical robotics. While deep learning architectures have rapidly …

Purpose Computer-assisted surgical systems provide support information to the surgeon,
which can improve the execution and overall outcome of the procedure. These systems are …

The ability to recover tissue deformation from visual features is fundamental for many robotic
surgery applications. This has been a long-standing research topic in computer vision …

The lack of large datasets and high-quality annotated data often limits the development of
accurate and robust machine-learning models within the medical and surgical domains. In …

Recent advancements in surgical computer vision applications have been driven by fully-
supervised methods, primarily using only visual data. These methods rely on manually …