Course summary
Medical imaging is the technology that allows us to see inside the human body without surgery. This involves techniques such as MRI, CT, ultrasound, and advanced digital imaging. Using these clinicians can detect disease earlier and plan treatments with precision. They can also monitor how well therapies are working. Medical imaging plays a vital role in modern healthcare. It supports accurate diagnosis, improves patient outcomes, and guides life-saving decisions. Artificial intelligence (AI) is reshaping every part of healthcare. By analysing large sets of medical data, AI can recognise patterns that are too complex or subtle for humans to detect. In imaging, AI systems can enhance image quality and detect abnormalities automatically. It can also support clinical decisions, and streamline workflows. AI is not replacing clinicians. It is becoming a powerful tool that helps them work faster, more accurately, and with greater confidence. When combined, medical imaging and AI create one of the most exciting frontiers in modern medicine. AI-driven image analysis can speed up diagnosis, reduce human error, and expand healthcare access around the world. This intersection is driving breakthroughs in healthcare. These range from early cancer detection to personalised treatment planning. These all have a positive impact on patient care. In this course, you will learn how imaging science, advanced technology, and AI algorithms come together. You will see how they come together to solve real clinical problems. Instead of studying these areas in isolation, you will think across imaging physics, computational methods, and clinical decision-making. This mirrors how innovation happens in modern medical imaging. You will build a number of practical skills. This will be done through hands-on labs, project-based learning, and exposure to real imaging workflows. You will learn to:
- understand and optimise imaging techniques, including MRI, CT, ultrasound, and multimodal systems
- apply AI and machine learning to images, signals, and clinical datasets
- understand quantitative imaging, segmentation, reconstruction, and computer-assisted diagnosis
- evaluate imaging technologies in clinical environments. You will also learn to understand their diagnostic impact
- navigate regulatory, safety, and ethical requirements in imaging and AI development
- working effectively with radiologists, physicists, engineers, and AI specialists. This will allow you to design clinically relevant solutions
- medical imaging companies
- AI healthcare organisations
- the NHS
- research institutes
- start-ups
- international health technology sectors
Assessment method
You will be assessed through a combination of coursework and end-of-semester exams.
Entry requirements
A UK Lower Second-Class Honours (2:2) degree. Your degree should be in a relevant engineering, physical science or medical discipline. Applicants with clinical medicine and radiography qualification may also considered depending on math and physics content of their degree qualification. You may also apply of your are able to demonstrate appropriate professional experience.
Fees and funding
Tuition fees
| England | £13230 | Year 1 |
| Northern Ireland | £13230 | Year 1 |
| Scotland | £13230 | Year 1 |
| Wales | £13230 | Year 1 |
| Channel Islands | £13230 | Year 1 |
| Republic of Ireland | £13230 | Year 1 |
| EU | £28750 | Year 1 |
| International | £28750 | Year 1 |
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Tuition fees shown are for our one year taught postgraduate degrees starting in 2026/7.
Tuition fees for International students will increase by no more than either of the below, whichever is higher at September of the relevant academic year:
a 5% increase on the previous year’s tuition fee for your programme of study
an increase in accordance with the Consumer Prices Index
Provider information
University of Dundee
Nethergate
Dundee
DD1 4HN