Object With the development of deep learning, the number of training samples for medical
image-based diagnosis and treatment models is increasing. Generative Adversarial …

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

In conventional robot-assisted minimally invasive procedures (RMIS), surgeons have narrow
visual and complex working spaces, along with specular reflection, blood, camera-lens …

The semantic segmentation of robotic surgery video and the delineation of robotic
instruments are important for enabling automation. Despite major recent progresses, the …

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 plays a crucial role in robot-assisted surgery by furnishing
essential information about instrument location and orientation. This information not only …

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

The increasing efficiency and compactness of deep learning architectures, together with
hardware improvements, have enabled the complex and high-dimensional modelling of …

Abstract Introduction Artificial Intelligence (AI) has shown promise in facilitating surgical
video review through automatic recognition of surgical activities/events. There are few public …

Deep Neural Networks (DNNs) based semantic segmentation of the robotic instruments and
tissues can enhance the precision of surgical activities in robot-assisted surgery. However …