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Contact information


qiang.zhang@cardiov.ox.ac.uk

Qiang Zhang

PhD, FSCMR

Associate Professor of AI in Cardiovascular Imaging

  • British Heart Foundation Intermediate Fellowship
  • Deputy Lead, RDM AI and Medical Big Data CCRT

I am a deep learning (machine learning) scientist, with cross-domain knowledge of cardiovascular disease, MR physics and scan protocols. My research programme focuses on (i) advancing cardiac imaging and (ii) enriching clinical research, with AI:

(i)   Advancing cardiovascular MRI with Generative AI. A representative work is Virtual Native Enhancement (VNE) imaging, where we developed AI techniques that could serve as "virtual contrast" in enhancing MR images, without the need for contrast injections. This may lead to more informative, needle-free, faster and safer heart MR scans.

(ii)   Developing automated image processing pipeline for cardiac imaging big data, and AI-enhanced cardiac biomarkers to drive new discoveries in clinical research.

In the press

News articles

• RDM News: "First real-world trial shows AI could reduce contrast injections ...", 15 Jul 2026
• The Sunday Times: "AI slashes cost of MRI scans ...", 1 Jan 2023
• Oxford University News: "How AI is shaping medical imaging", 20 Sep 2022
• RDM News: "SCMR Early Career Award" 8 Feb 2022
• BHF News: "AI breakthrough for faster, cheaper and injection-free heart scans", 9 Aug 2021
• The Telegraph: "New AI heart scanner will cut NHS backlog ...", 7 Aug 2021
• SCMR Newsletter, 29 Jul 2021
• OUH News: "AI replaces contrast dye for fast, cheaper ...", 8 Jul 2021
• RDM News "AI breakthrough for fast and cheaper CMR scans", 7 Jul 2021
• NIHR Oxford BRC News: "AI replaces contrast dyes for needle-free CMR", 7 Jul 2021

Interview

BBC Radio 4 Today Interview, on how new AI technologies can help with NHS backlog, 9 Aug 2021
Times Radio Interview, on AI and robotics in healthcare, 10 Aug 2021