PhD project in generative AI for cardiac imaging
Monday 7th October 2024
Contact Email for the Job Positing [email protected]
Organization University of Oxford
Location John Radcliffe Hospital, Oxford, UK
Title PhD project in generative AI for cardiac imaging
URL https://www.rdm.ox.ac.uk/graduate-study/how-to-apply/supervisor-profiles/zhang-group-generative-artificial-intelligence-for-cardiovascular-imaging
Closing date Dec 04, 2024
Description This DPhil project (2025 entry) aims to develop novel generative AI to enhance cardiac MRI to assess myocardial pathologies beyond the current diagnostic capabilities of MRI. You will focus on one of the three research questions:
(1) Beyond detecting focal scar (as discovered in the pilot work Circulation 2021, 2022 [1][2]), can AI-enhancement capture crucially important diffuse myocardial pathologies without contrast injections?
(2) How to develop stable, generalisable and explainable models for AI-enhancement of MRI for reliable clinical use?
(3) Can AI-enhancement provide new imaging biomarkers beyond conventional MRI, for risk prediction of important clinical outcomes (such as sudden death) in large-scale clinical studies?
This student project is expected to contribute to our compressive programme working towards disruptive, AI-based cardiac MRI technologies, as robust diagnostic tools for in-depth heart imaging. You may also explore novel machine learning solutions for generative models, federated and transparent deep learning that are reliable for clinical use.
Training Opportunities
You will benefit from an interdisciplinary core supervision team of machine learning scientist, cardiologist (Prof. Vanessa Ferreira) and MR scientist (Prof. Stefan Piechnik), and develop deep generative models at the forefront of cardiac clinical research, immersed in hospital settings.
You will have the chance to observe real-world clinical MR scans, and access to facilitates at Oxford Big Data Institute. Additional training in machine learning is supported by Oxford Institute of Biomedical Engineering (Prof. Konstantinos Kamnitsas).
Students are encouraged to attend the MRC Weatherall Institute of Molecular Medicine DPhil Course, which takes place in the autumn of their first year. Running over several days, this course helps students to develop basic research and presentation skills, as well as introducing them to a wide range of scientific techniques and principles, ensuring that students have the opportunity to build a broad-based understanding of differing research methodologies.
Generic skills training is offered through the Medical Sciences Division's Skills Training Programme. This programme offers a comprehensive range of courses covering many important areas of researcher development: knowledge and intellectual abilities, personal effectiveness, research governance and organisation, and engagement, influence, and impact. Students are actively encouraged to take advantage of the training opportunities available to them.
As well as the specific training detailed above, students will have access to a wide range of seminars and training opportunities through the many research institutes and centres based in Oxford.
The Department has a successful mentoring scheme, open to graduate students, which provides an additional possible channel for personal and professional development outside the regular supervisory framework. We hold an Athena SWAN Silver Award in recognition of our efforts to build a happy and rewarding environment where all staff and students are supported to achieve their full potential.
Additional Supervisors
Professor Stefan Piechnik
Professor Vanessa Ferreira
Professor Konstantinos Kamnitsas
References
1. https://doi.org/10.1161/CIRCULATIONAHA.121.054432
2. https://doi.org/10.1161/CIRCULATIONAHA.122.060137
3. https://doi.org/10.1016/j.jocmr.2024.101051
4. https://www.ox.ac.uk/news/features/how-artificial-intelligence-shaping-medical-imaging
5. https://www.telegraph.co.uk/news/2021/08/07/new-ai-heart-scanner-will-cut-nhs-backlog-half-delivering-results/
6. https://www.bhf.org.uk/what-we-do/news-from-the-bhf/news-archive/2021/august/ai-breakthrough-for-faster-cheaper-and-injection-free-heart-scans