Multi-source Platform
- The multi-source collaborative learning data platform will establish a research-focused framework in the NHS.
- A CRUK RadNet AI and Computational Modelling working group has been established to coordinate, promote and share AI methods and opportunities across RadNet and beyond, maximising excellence and the broader impact in radiotherapy.
Lead
Mr Bob Wheller (Co-Lead)
Head of Radiotherapy Technology Services
Bob is a chartered engineer responsible for a group of 27 clinical engineering staff providing electronic, computing and mechanical engineering support, primarily to the large radiotherapy service at Leeds Teaching Hospitals NHS Trust. Clinical engineering services include equipment management, device design and development, clinical computing and technical logistics.
His professional Interests include: clinical computing – utilising medical equipment data to improve clinical practice; improving the interoperation of medical equipment; improving training and development across the clinical engineering workforce; optimising medical equipment contracting arrangements and focusing clinical engineering on patient care through clinical engagement.
Imaging
- A new MRI Sim will be installed on the radiotherapy treatment floor and will provide ring-fenced capacity for research.
- A concise set of image acquisition and data analysis tools are being developed to characterise tumour and normal tissue for radiotherapy treatment planning, response monitoring and outcome prediction.
Leads
Professor Andy Scarsbrook (Co-Lead)
Honorary Professor of Radiology
Staff profile: Professor Andy Scarsbrook | School of Medicine | University of Leeds
Professor David Buckley (Co-Lead)
Professor of Medical Physics
Staff profile: Professor David L. Buckley | School of Medicine | University of Leeds
Computational Modelling and Analytics
- Physiological and data-driven modelling and analysis tolls are being developed in collaboration with the Computational Imaging and Simulation Technologies in Biomedicine (CISTIB).
- Deep learning approaches are being deployed in conjunction with biomechanical modelling and our large retrospective imaging datasets to create new tolls for patient motion characterization.
Lead
Dr Zeike Taylor (Co-Lead)
Associate Professor in Mechanical Engineering
Staff profile: Dr Zeike Taylor | School of Mechanical Engineering | University of Leeds