Real-time Data Fusion for Image-guided Fetal Surgery
UCL was recently awarded £10million to develop better tools and imaging techniques that will improve the success of surgery and other therapies on unborn babies in collaboration with KU Leuven, Great Ormond Street Hospital and University College London Hospital. As part of this widely scoped endeavour, different imaging modalities such as pre-operative MR, real-time ultrasound and intra-operative photoaccoustics will be introduced to guide the surgery. While
the addition of imaging sources may provide decision-changing information, there’s a clear need for computational tools that would help the physician in correlating these images and fusing them for efficient surgery guidance. While image fusion is a very active field of research, developing it for fetal surgery poses major methodological challenges due to the large movements that
may occur between the pre-operative images and the intra-operative ones but also during the surgery itself. This PhD project will consider new methodologies for image fusion by borrowing models and concepts from medical image registration, computer vision and machine learning. Candidates with a strong interest in the following areas are encouraged to apply: medical image registration, statistical/machine learning, computer vision, and translational applications of medical image computing, real-time image processing.