2026 Piechnik Group: Experimental and clinical translation of advanced quantitative cardiovascular magnetic resonance imaging techniques

About the Research 

OCMR has an international reputation for cardiac MRI (CMR) research on all aspects from acquisition biophysics to clinical applications. The Advanced Cardiovascular Image Analysis group works together with OCMR core lab analysts and clinicians at the frontline CMR clinical facility. We address wide range of pressing practical needs of individual clinical researchers locally and large external clinical studies. Our focus is on improving and standardization of quantitative CMR approaches to support better healthcare.

We lead the CMR cardiac tissue characterisation research in the field called T1 mapping. The techniques pioneered in OCMR brought a wide range of publications on technical aspects and clinical application regarding many yet unexplained relations between novel clinical and imaging biomarkers. We actively engage in big biomedical data aspects, and develop artificial intelligence approaches to address broad and unmet clinical needs, including automated medical image analysis, quality control and novel contrast enhancement mechanisms. We also support projects involving on-scanner programming to integrate AI with MRI platforms for clinical validation and adoption, in close collaboration with our industrial partners. A wide range of potential projects can also be customised to match skills of interested candidates, such as biomedical imaging, MR scanning and sequence development. Many of our methods, especially the most recent developments using artificial intelligence are in urgent need to deploy and validate on clinical scanners. Experience or transferrable skills and willingness to develop methods directly on clinical scanners are key to this project.

Additional supervision may be provided by Associate Professor Vanessa Ferreira, Professor Qiang Zhang, Dr. Peter Gatehouse.

Training Opportunities

New members joining this multidisciplinary group are usually experts in either technical or bio-medical science. We expect experience in programming, machine learning, or MR physics, particularly with application to medical imaging. We provide compatible hands-on training and advice to complement a specific set of skills required to complete work on the agreed research topic, e.g. as may be necessary for implementing the methods directly on clinical scanners in collaboration with scanner vendors. Needs are assessed termly on an individual basis, making use of an excellent selection of courses organised at Oxford University and externally.

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

1. Vanessa Ferreira 

2. Qiang Zhang 

3. Peter Gatehouse

Publications