Research Projects Available
DPhil
- 2026 Raman Group: Pioneering Precision Medicine in Hypertrophic Cardiomyopathy: Advanced Imaging, Machine Learning, and Translational Research for Early Detection and Targeted Therapies — Radcliffe Department of Medicine
- 2026 Raman Group (MRC Enterprise iCase): Development of Cardiac Diffusion Tensor Imaging for Clinical Evaluation of Cardiomyopathies — Radcliffe Department of Medicine
MSc by Research
- Raman Group: Intergrating Multimodal Imaging, Genomics, and Clinical Data for Risk Stratification and Precision Therapy in Cardiomyopathies through Novel Artificial Intelligence Approaches — Radcliffe Department of Medicine
- Raman Group: Multi-Organ MRI Phenotyping for Risk Prediction in Heart Failure and Multisystem Diseases: Insights from Prospective Imaging Cohorts and UK Biobank — Radcliffe Department of Medicine
- Raman Group: AI-Enhanced ECG and Digital Twin Modelling for Early Diagnosis and Mechanistic Stratification in Cardiomyopathies — Radcliffe Department of Medicine
- Raman Group: Unravelling Mechanisms of Phenotypic Diversity in Hypertrophic Cardiomyopathy through Advanced Cardiac MRI and Patient-Specific Multi-Omic Modelling — Radcliffe Department of Medicine
- Raman Group: Enhancing Traditional and Photon-Counting CT for the Early Diagnosis and Phenotyping of Cardiomyopathies — Radcliffe Department of Medicine
Colleges
Websites
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Sky news
Findings from the C-MORE - multiorgan MRI Study
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BBC news
Findings from the C-MORE - multiorgan MRI Study
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BBC world radio
Betty Raman presenting findings from the C-MORE study (8:20)
Betty Raman
MBBS DPhil FESC FRACP
Associate Professor of Cardiovascular Medicine
- NIHR South Central RRDN Cardiology Specialty Lead
- Hon. Consultant Cardiologist (Loc)
- Wellcome Career Development Award Fellow
- RDM Cardiovascular Medicine EDI Champion
Prof Betty Raman is a senior honorary consultant cardiologist specialising in advanced cardiovascular imaging (CMR and cardiac CT) and inherited and cardiomyopathic heart disease. She leads a translational research programme that bridges mechanistic discovery, clinical application, and innovation in drug development.
After completing her specialist cardiology training in Australia (FRACP), she joined the University of Oxford in 2015 to pursue a DPhil in hypertrophic cardiomyopathy, the leading cause of sudden cardiac death in young adults and athletes. Her doctoral work led to the development of a novel oxygen sensitive magnetic resonance method that detects myocardial hypoxia non-invasively and holds promise as an early biomarker of disease activity. This pioneering work has been recognised internationally through awards from the ESC, AHA, BSCMR, SCMR, and BCS.
Building on this foundation, she was awarded a British Heart Foundation Transition Fellowship (2020) and subsequently a Wellcome Career Development Award (2024) to advance a multidisciplinary research programme integrating imaging, genetics, energetics, and computational modelling. Her goal is to identify and validate early markers of disease progression in hypertrophic and related cardiomyopathies, enabling more precise risk prediction and supporting evaluation of emerging therapies.
During the COVID 19 pandemic, she led the C-MORE study, a large multicentre initiative that combined MRI, cardiopulmonary exercise testing, and cognitive assessments to characterise the long term multi organ consequences of COVID 19. This work helped shape understanding of post-viral cardiovascular and systemic recovery.
Her current research focuses on:
Early stage disease detection and monitoring in cardiomyopathies using next generation CMR including BOLD, DTI, spectroscopy, and radiomics.
Mechanistic biomarkers to support early phase and adaptive clinical trials.
Cross organ interactions in cardiometabolic disease, integrating heart, brain, liver, and renal imaging.
As a senior academic leader, she collaborates widely across academia, the NHS, and industry to translate advanced imaging into clinical and commercial impact. She actively welcomes scientific collaborators, students, and industrial partners interested in biomarker discovery, imaging enabled trial design, and AI based modelling for cardiovascular disease.
