Today, minimally invasive surgery is increasingly used in various operations. Compared
with traditional surgery, minimally invasive surgery makes patients less painful and recovers …

Background: Lack of anatomy recognition represents a clinically relevant risk in abdominal
surgery. Machine learning (ML) methods can help identify visible patterns and risk …

Background Small bowel adenocarcinoma is a relatively rare cancer, often diagnosed in an
advanced stage. In localized and resectable disease, surgery alone or in combination with …

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 …

The ability to automatically detect and track surgical instruments in endoscopic videos can
enable transformational interventions. Assessing surgical performance and efficiency …

Deep Learning (DL) has achieved robust competency assessment in various high-stakes
fields. However, the applicability of DL models is often hampered by their substantial data …

To ensure satisfactory clinical outcomes, surgical skill assessment must be objective, time-
efficient, and preferentially automated—none of which is currently achievable. Video-based …

This paper presents a method for endoscope's autonomous positioning by a robotic
endoscope holder for minimally invasive surgery. The method improves human-robot …

Pose estimation is a necessity for many applications in robotics incorporating interaction
between the robot and external camera-equipped devices, eg mobile robots or Augmented …

Surgical tool detection in minimally invasive surgery is an essential part of computer-
assisted interventions. Current approaches are mostly based on supervised methods …