Dr Niloufar Zarinabad PhD, AFHEA

Dr Niloufar Zarinabad

Institute of Cancer and Genomic Sciences
NIHR Research Fellow

Contact details

Institute of Cancer and Genomic Sciences
College of Medical and Dental Sciences
University of Birmingham
B15 2TT

Dr Zarinabad is a Senior Research Fellow at the University of Birmingham’s Children's Brain Tumour Research Team based at the Birmingham Children’s Hospital.

The group are developing advanced functional imaging techniques for the diagnosis, understanding and management of childhood brain tumours.

Her main research interests include biomedical signal processing, medical imaging; image guided therapy and translational research. 


  • Ph. D. in Imaging Science and Biomedical Engineering, King’s College London ,2013
  • M.Sc. in Signal Processing, King’s College London, 2009
  • B.Sc. in Electrical Engineering, 2007
  • Postgraduate certificate in higher education (PGCAPHE), Kings College London, 2016


Dr. Niloufar Zarinabad obtained her master‘s in Signal processing in 2009 from Kings College London. From 2009 to 2013, she studied for a doctorate in the Division of Imaging Sciences and Biomedical Engineering, King’s College London, investigating quantitative cardiac blood flow analysis using Magnetic Resonance Imaging. During this time, she worked in close collaboration with industry to extend these techniques.

From May 2013 to January 2015, Dr. Zarinabad was employed at the Division of Imaging Sciences, King’s College London as a post-doctoral researcher where she developed a research interest in the field of image guided therapy and translational research. In January 2015, she was appointed as a Senior Research Fellow within the University of Birmingham’s Children's Brain Tumour Research Team. Funded via NIHR, the role includes firstly developing a clinical decision support system based on advanced machine learning and signal processing techniques and secondly leading translational projects to see the latter through.  

Postgraduate supervision

Co-Supervisor for PhDs

  • 1 current 


Niloufar’s current research project includes the development, implementation and evaluation of a decision support system for a personalised diagnostic pipeline of childhood brain tumours. The use of refined interpretation of medical data enables characterisation, grading and classification of rare tumours. 

 At King’s College London, Niloufar was responsible for the design, development and validation of an automated myocardial perfusion quantification tool that facilitates clinical decision making in the management of coronary artery disease. This decision support aid is currently in use within clinical myocardial perfusion research groups.


1. Zarinabad N, Hautvast GL, Breeuwer M, Nagel E, Chiribiri A,(2014), Effects of tracer arrival time on the accuracy of high resolution (voxel-wise) myocardial perfusion map from contrast-enhanced first-pass perfusion magnetic resonance, IEEE Transaction of Biomedical Engineering, 61(9):2499-506.

2. Zarinabad N, Hautvast GL, Breeuwer M, Nagel E, Chiribiri A, (2015),Influence of spatial resolution on the accuracy of quantitative myocardial perfusion in first pass stress perfusion CMR,” Magnetic Resonance in Medicine, 73(4):1623-31.

3. Zarinabad N, Chiribiri A, Hautvast GL, Ishida M, Schuster A, Cvetkovic Z, Batchelor PG, Nagel E, (2012), Voxel-wise quantification of myocardial perfusion by cardiac magnetic resonance. Feasibility and methods comparison.,Magnetic Resonance in Medicine, 68(6):1994-2004.

4. Zarinabad N, Chiribiri A, Breeuwer M, (2014), Myocardial blood flow quantification from MRI – an image analysis perspective, Current Cardiovascular Imaging Reports, Springer, 7:9246.

5. Hautvast G, Chiribiri A, Zarinabad N, Schuster A, Breeuwer M, Nagel E , (2012), Myocardial blood flow quantification from MRI by deconvolution using an exponential approximation basis., IEEE Transaction of Biomedical Engineering, 59(7):2060-7.

6. Chiribiri A, Schuster A, Ishida M, Hautvast G, Zarinabad N, Morton G, Otton J, Plein S, Breeuwer M, Batchelor P, Schaeffter T, Nagel E, (2013),  Perfusion phantom: An efficient and reproducible method to simulate myocardial first-pass perfusion measurements with cardiovascular magnetic resonance.,  Magnetic Resonance in Medicine, 69(3):698-707.

7. Schuster A, Sinclair M, Zarinabad N, Ishida M, van den Wijngaard JP, Paul M, van Horssen P, Hussain ST, Perera D, Schaeffter T, Spaan JA, Siebes M, Nagel E, Chiribiri A, (2015), A quantitative high resolution voxel-wise assessment of myocardial blood flow from contrast-enhanced first-pass magnetic resonance perfusion imaging: microsphere validation in a magnetic resonance compatible free beating explanted pig heart model., Eur Heart J Cardiovasc Imaging, 16(10):1082-92.

8. Fetit AE, Khan O, Afyouni S, Zarinabad N, Novak J, Peet AC, Arvanitis TN ,(2015), An Extensible Neuroimaging e-Repository for Clinical Trials of Paediatric Brain Tumours., Stud Health Technol Inform, 213:49-52. 

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