Imperial College London


Faculty of MedicineNational Heart & Lung Institute

Honorary Research Fellow







Sydney StreetRoyal Brompton Campus





I am a Senior Image Processing and Data Scientist based at the Cardiovascular Magnetic Resonance unit, Royal Brompton Hospital. I have a background in Physics and Mathematics, a PhD in MRI Physics (Imperial College :: London), and an extensive experience in MRI research.

Since 2012, I have been working closely with a team of physicists and clinicians in diffusion tensor cardiovascular magnetic resonance (DT-CMR). It is a novel technique for the investigation of the 3-dimensional microstructure of the heart in-vivo. We aim to improve the understanding of how the healthy heart functions as well as how microstructural dysfunction contributes to disease.

I am focused on creating specialised tools to perform data analysis, image processing, and data visualisation, with a recent interest in finding solutions with AI.

Left ventricle tractography


We developed and validated a fully automated postprocessing framework for in vivo diffusion tensor cardiac magnetic resonance (DT-CMR) data powered by deep learning semantic segmentation (TensorFlow):

  • U-Net architecture
  • Proposed fully automated post-processing pipeline

We published in vivo studies showing that secondary directions of diffusion align with the laminar organisation of cardiomyocytes in the heart, and that cardiomyopathy hearts present impaired mobility:

sheetlet rotation

 Previous academic education:

  • 2005 - 2009: PhD in Myocardial Perfusion Imaging with MR, Imperial College, London, UK.
  • 2004 - 2005: MSc in Medical Engineering and Physics, King’s College, University of London, UK.
  • 1998 - 2004: First Degree in Physics / Applied Mathematics (Astrophysics), Faculty of Sciences, University of Porto, Portugal.



Teh I, Romero W, Boyle J, et al., 2022, Validation of cardiac diffusion tensor imaging sequences: A multi-centre test-retest phantom study, Nmr in Biomedicine, Vol:35, ISSN:0952-3480, Pages:1-18

Ferreira PF, Banerjee A, Scott AD, et al., 2022, Accelerating Cardiac Diffusion Tensor Imaging With a U-Net Based Model: Toward Single Breath-Hold, Journal of Magnetic Resonance Imaging, Vol:56, ISSN:1053-1807, Pages:1691-1704

Auger DA, Ghadimi S, Cai X, et al., 2022, Reproducibility of global and segmental myocardial strain using cine DENSE at 3 T: a multicenter cardiovascular magnetic resonance study in healthy subjects and patients with heart disease, Journal of Cardiovascular Magnetic Resonance, Vol:24, ISSN:1097-6647, Pages:23-23

Dwornik M, Khalique Z, Rajakulasingam R, et al., 2022, Cardiovascular Magnetic Resonance in Cardiomyopathy, International Journal of Cardiodiabetes

Scott A, Jackson T, Khalique Z, et al., 2022, Development of a CMR compatible large animal isolated heart model for direct comparison of beating and arrested hearts, Nmr in Biomedicine, Vol:35, ISSN:0952-3480

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