Applying fast machine learning to medical imaging

This project will explore the translation of machine learning algorithms developed on FPGAs/GPUs/CPUs for particle physics data selection to the field of medical imaging. It will explore how real-time analysis and feedback could lead to improved patient diagnosis and care, with a particular focus on neurovascular applications, intra-operative image analysis, “on-the-fly” image analysis during scanning, as well as adaptive image protocols e.g. for CT/MRI scans.