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Zhang Group: Artificial Intelligence in Cardiovascular Medicine

  • Division of Cardiovascular Medicine
  • Oxford Centre for Clinical Magnetic Resonance Research

We work with clinician, MR scientists and health statisticians on a day-to-day basis to develop novel AI machine-learning approaches for cardiovascular medicine.

The Group’s primary aim is to advance cardiac diagnostic imaging and enrich cardiovascular clinical studies through the deep integration of AI machine learning with MRI and cardiology. In particular:

  • Make cardiovascular MRI scanning safer, faster and more informative by enhancing the image contrast with novel generative AI approaches. A representative work is the Virtual Native Enhancement technology.
  • Automate the cardiovascular MRI post-processing and reporting using pipelines empowered by feature detection, registration, segmentation and LLM machine-learning methods.
  • Enrich large biomedical studies with novel AI imaging biomarkers and machine-learning tools, through collaborations with the BHF Oxford CRE network, Big Data Institute, and RDM AI and Medical Big Data CCRT. 

Team members at the Big Data Institute:

  •  Jun Li - OxPop DPhil student, AI machine learning for cardiac population health.

DPhil Projects available will appear below

Our team

COLLABORATORS

  • Prof Thomas Nichols, Big Data Institute, University of Oxford
  • Prof Konstantinos Kamnitsas, Institute of Biomedical Imaging, University of Oxford
  • Prof Sven Plein, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds
  • Prof Rohan Dharmakumar, Krannert Cardiovascular Research Center, Indiana University, USA
  • Prof Steffen Petersen, Queen Mary University of London, NIHR Barts Biomedical Research Centre (BRC)
  • Prof Minjie Lu, National Centre for Cardiovascular Diseases (NCCD), Chinese Academy of Medical Science, China