Contact information
Colleges
Qiang Zhang
PhD, FSCMR
Associate Professor of AI in Cardiovascular Imaging
- British Heart Foundation Intermediate Fellowship
- British Heart Foundation CRE Transition Fellowship
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.
[new] I am starting a Deep Learning Group at the Division of Cardiovascular Medicine, and will be actively recruiting for post-doctoral researchers and DPhil (PhD) students. Contact me for more information.
In the press
News articles
• 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
Editorial
Circulation Podcast, 24 Aug 2021
Circulation Podcast, 15 Nov 2022
Circulation Editorial, 2021
Circulation Editorial, 2022
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
Key publications
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Journal article
Zhang Q. et al, (2024), J Cardiovasc Magn Reson
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Journal article
Zhang Q. et al, (2021), Circulation, 144, 589 - 599
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Journal article
Zhang Q. et al, (2022), Circulation, 146, 1492 - 1503
Recent publications
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Generative AI Virtual Contrast for Cardiovascular Magnetic Resonance: A Pathway to Needle-Free and Fast Imaging of Myocardial Infarction?
Journal article
Fok WYR. and Zhang Q., (2024), Circ Cardiovasc Imaging
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Improving the efficiency and accuracy of CMR with AI - review of evidence and proposition of a roadmap to clinical translation.
Journal article
Zhang Q. et al, (2024), J Cardiovasc Magn Reson
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Deep learning for automated insertion point annotation of CMR T1 maps
Conference paper
Gonzales RA. et al, (2024)
Patents
Zhang Q, Piechnik SK, Ferreira VM, Hann E, Popescu IA: “Enhancement of Medical Images”, Oxford University Innovation, PCT/GB2020/052117, published 11 March 2021 (Publication number WO/2021/044153)
Zhang Q, Piechnik SK, Ferreira VM, Werys K, Popescu IA: “Validation of Quantitative Magnetic Resonance Imaging Protocols”, Oxford University Innovation, PCT/GB2020/051189, published 26 Nov 2020 (Publication number WO/2020/234570)
Hann E, Piechnik SK, Popescu IA, Zhang Q, Werys K, Ferreira VM: “Method and Apparatus for Quality Prediction”, Oxford University Innovation, PCT/GB2020/050249, published 13 Aug 2020 (Publication number WO/2020/161481)