MSc Artificial Intelligence and Medical Imaging

This one-year Master’s will give you specialist expertise in the latest imaging technologies and AI methods, so you can play your part in improving disease detection and diagnosis, and help patients benefit from the treatments they need most. This MSc covers the core technology and applications of the latest medical imaging tools currently available in healthcare, as well as new developments – and the valuable data and analysis that can be extracted from them. You will explore core methods and techniques in both AI and medical imaging, and undertake your own piece of research to put your skills into practice working on clinically relevant problems. Explore topical challenges like medical image segmentation, quantifying pathological regions in medical images, improving imaging based diagnosis and treatment response prediction, working alongside UCL’s researchers who are helping to shape and influence new developments in this exciting field. There’s a lot of flexibility too, with the chance to add in optional modules. The programme spans the departments of UCL Medical Physics and Biomedical Engineering and UCL Computer Science, so you can focus on computing, study AI and computational modelling in surgery, or learn more about med-tech entrepreneurship if you’re interested in exploring a start-up career path. This course is for you if you have a background in computer science, engineering or a related field, and are looking to deepen your knowledge and specialise in applying it to healthcare. It’s particularly relevant if you enjoy problem-solving and innovating, and are interested in redefining what’s possible in healthcare with the goal of improving patient lives through AI and medical imaging.

A minimum of an upper second-class Bachelor’s degree in Computer Science, Engineering, Physics or related fields from a UK university or an overseas qualification of an equivalent standard. Undergraduate level knowledge in programming languages (such as Python or C++) is essential, demonstrated, e.g., by relevant courses or by an individual project they worked on during their UG. Undergraduate level knowledge of mathematics is also required, in algebra, analysis and probability. Applicants must show an interest in developing thinking and problem-solving skills.