Hamlyn Winter School on Surgical Imaging and Vision
Applications for the 2021 Winter School will open in October.
Surgical Imaging and Vision is a growing area of research and an integral part of every endeavour in Robotic Surgery. It has advanced from a pre-operative planning and post-operative assessment tool to emerging platforms for intra-operative guidance and navigation. Advances in imaging have enabled the development of new modalities beyond the conventional whole-body techniques such as MR, CT and US to enable in vivo, in situ tissue characterisation by the use of biophotonics techniques that can be integrated with robotic instruments. The development of 3D vision facilitates structural-functional fusion, accurate focused energy delivery, large-area in vivo microscopic imaging, motion adaptation, visual servoing, and navigation under dynamic active constraints. All these are important for the development of new surgical robots for minimally invasive surgery.
The Hamlyn Winter School on Surgical Imaging and Vision is a week long course, held in the beginning of December each year. Participants should have a science or medical degree and typically be at a master, doctoral or postdoctoral level.
The Hamlyn Winter School focuses on both the technical and clinical aspects of Surgical Imaging and Vision. Through invited lectures, workshops, and mini-projects, the purpose of our winter school is to help researchers familiarise with the cutting edge research of this rapidly expanding field covering key areas of:
- Fundamentals and current state-of-the-art in surgical imaging;
- Vision algorithms for tracking, 3D scene reconstruction and surgical navigation;
- Intra-operative registration and retargeting;
- Multi-modal image fusion and real-time augmented reality systems based on inverse realism;
- Robot assisted large area microscopic imaging and mosaicing;
- Dynamic active constraints with real-time vision;
- Vision enabled surgical robot design and miniaturisation.
You can view last year's programme for more information here.