Surgical data science and team mission
Surgical Data Science (SDS) is about improving outcomes of surgery with AI-based software systems driven by clinical data. We aim to improve the training and capabilities of surgical teams with SDS, to reduce complications, make surgery easier and safer, and achieve better patient outcomes.
Ultrasound (US) is a key technology to detect abdominal cancer early, and treat it with minimal intervention. The disrumpere project aims to combine low-cost ultrasound devices with innovative AI and robotics technologies, to make US easier, faster more widely used.
Laparoscopic surgical guidance systems with Augmented Reality
We research computer systems to improve laparoscopic surgery with Augmented Reality (AR) technologies. 3D medical image data such as CT or MR is automatically combined with the laparoscopic video, to show hidden critical structures such as tumours and major vessels.
Percutaneous surgical guidance systems
We research computer systems to improve percutaneous surgery with Virtual Reality (VR) and 3D tracking technologies.
Ultrasound and flexible endoscopy educational systems
Objective skill assessment is becoming an increasingly important component of surgery education and high-stakes skill assessment for accreditation. Our goal is to combine low-cost mechanical simulators with AI to make these tools broadly accessible.
Most of our applications are built with Sight, the Surgical Image Guidance and Healthcare Toolkit. Sight aims to facilitate the creation of software based on medical imaging and is freely available in open-source.
Clinical and technical publications
Mixed reality navigation system for ultrasound-guided percutaneous punctures: a pre-clinical evaluation
Artificial intelligence and surgery: Recent progress and future perspectives
Automatic task recognition in a flexible endoscopy benchtop trainer with semi-supervised learning
Light modelling and calibration in laparoscopy
Assistance to trajectory planning and needle guiding for percutaneous surgery.