Imperial College London

ProfessorDavidFirmin

Faculty of MedicineNational Heart & Lung Institute

Emeritus Professor of Biomedical Imaging
 
 
 
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Contact

 

+44 (0)20 7351 8801d.firmin

 
 
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Location

 

Cardiovascular MR UnitRoyal Brompton Campus

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Summary

 

Summary

David Firmin is Professor of Biomedical Imaging at the National Heart and Lung Institute, Imperial College London, and the Physics Director of the Royal Brompton Hospitals CMR Unit.

His involvement in Cardiovascular MR began in 1982 and he is one of the founding members of the Royal Brompton Unit which opened in 1984.  His major contribution to MRI has been in the development of quantitative phase contrast velocity imaging.

As the Director of Physics he has also led a number of pioneering advances in atheroma imaging, rapid and interactive cardiovascular MR, coronary angiography, myocardial perfusion imaging and tissue characterisation. 

Professor Firmin has served on many scientific programme committees and in 1999 he organised a highly successful ISMRM Workshop on Flow & Motion in Cardiovascular MR and recently, in recognition of his service, he has been made a Fellow of ISMRM.  He is an Assistant Editor of the Journal of Cardiovascular MR, and a referee for several major international scientific journals, and a former panel member of the Wellcome Trust Infrastructure Grant.

Professor Firmin has more than 350 publications in cardiovascular MR imaging, including over 170 peer reviewed academic journal papers.

Publications

Journals

Fair MJ, Gatehouse PD, Firmin DN, 2021, Minimisation of slab-selective radiofrequency excitation pulse durations constrained by an acceptable aliasing coefficient, Magnetic Resonance Imaging, Vol:81, ISSN:0730-725X, Pages:94-100

Wu Y, Tang Z, Li B, et al., 2021, Recent advances in fibrosis and scar segmentation from cardiac MRI: A state-of-the-art review and future perspectives, Frontiers in Physiology, Vol:12, ISSN:1664-042X, Pages:1-23

Liu T, Gao Y, Wang H, et al., 2021, Association between right ventricular strain and outcomes in patients with dilated cardiomyopathy, Heart, Vol:107, ISSN:1355-6037, Pages:1233-1239

Yang G, Zhang H, Firmin D, et al., 2021, Recent advances in artificial intelligence for cardiac imaging, Computerized Medical Imaging and Graphics, Vol:90, ISSN:0895-6111

Chen J, Yang G, Khan H, et al., 2021, JAS-GAN: generative adversarial network based joint atrium and scar segmentations on unbalanced atrial targets, Ieee Journal of Biomedical and Health Informatics, ISSN:2168-2194

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