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We aim to further improve the clinical value of Cardiovascular Magnetic Resonance with application of advanced image analysis techniques.

CMR algorithmics

Our group brings together non-clinical researchers such as imaging scientists, engineers, and image analysts, to develop and translate technologies within the close proximity of clinical practice environment.

Associate Professor Stefan Piechnik’s research group builds on extensive experience in developing quantitative biomarkers, focusing now on quantitative aspects of the cardiac tissue characterisation. His research group leads the effort on standardising T1 mapping towards its wider clinical application beside the wide range of Cardiovascular Magnetic Resonance outputs related to the anatomy and function of the heart. To address the progressively increasing data challenges, we move the field from the current gold standard, manual and semi-automatic heart definition, towards fully automated approaches, with particular attention to the strict quality control appropriate for clinical applications. We believe that image analysis and computer vision techniques, in particular deep neural networks for segmentation tasks, as well as registration techniques for motion correction applications, can improve the clinical workflow, resulting in rapid and robust detection of the various forms of pathology.

Multidisciplinary collaboration is the trademark of research in this field. Beside drawing on material and know-how of many researchers locally in OCMR , we maintain active external links:

  • UK BioBank (Elena Lukaschuk), the largest ever population study, with regard to its cardiovascular imaging effort through collaboration with Professor Steffen Petersen from William Harvey Research Institute, QMUL within the dedicated the imaging consortium to address the vast needs of this project.
  • Institute of Biomedical Engineering (IBME), University of Oxford, (Iulia Popescu and Evan Hann) collaboration with Professor Vicente Grau on cardiac image analysis, in particular machine learning approaches, such as deep learning, with applications to cardiac imaging for large-scale studies of more than 100,000 subjects, with the aim of providing accurate diagnosis and personalised disease management.
  • The HCMR Registry (Konrad Werys and Qiang Zhang) is the biggest hypertrophic cardiomyopathy imaging trial where our group is developing novel outcome predictors based on T1 maps. The study is designed to address limitations in existing evidence to improve prognosis in hypertrophic cardiomyopathy.
  • Instytut Kardiologii (IKARD), Poland, (Konrad Werys) Development of new diagnostic tools together with a visiting student, Agata Kubik.
  • Beta3_LVH (Henrike Puchta) Clinical Trial which investigates the effect of a drug in preventing structural heart remodelling and therefore decreasing the risk of developing heart failure. In this project, we are responsible for processing and analysing MRI scans from all nine cetres across EU. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 634559.
  • Çanakkale Onsekiz Mart University (COMU), Turkey - Dr Ahmet Barutcu is a Consultant Cardiologist and visiting fellow. His focus is in the area of cardiac imaging. At University of Oxford he is working in particular on HCM and UK Biobank MR tagging data.
  • Industrial partners, such as Siemens Healthineers, Circle Cardiovascular Imaging, and Medis Cardiovascular Imaging.

Our team

Related research themes