Area of research
Radiology, Nuclear Medicine and Imaging · Cardiology and Cardiovascular Medicine
Research interest
Research interests include Cardiac Imaging and Diagnostics, Cardiovascular Function and Risk Factors, Advanced MRI Techniques and Applications, and Radiomics and Machine Learning in Medical Imaging.
Druggable proteins influencing cardiac structure and function: Implications for heart failure therapies and cancer cardiotoxicity
Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images
An artificial intelligence tool for automated analysis of large-scale unstructured clinical cine cardiac magnetic resonance databases
Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex and Racial Bias in Deep Learning-Based Segmentation
Prevalence and Disease Expression of Pathogenic and Likely Pathogenic Variants Associated With Inherited Cardiomyopathies in the General Population
Artificial Intelligence in Cardiac MRI: Is Clinical Adoption Forthcoming?
A multimodal deep learning model for cardiac resynchronisation therapy response prediction
Non-invasive localization of post-infarct ventricular tachycardia exit sites to guide ablation planning: a computational deep learning platform utilizing the 12-lead electrocardiogram and intracardiac electrograms from implanted devices
Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with uncertainty-based quality-control
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction
Fully Automated, Quality-Controlled Cardiac Analysis From CMR
Detection and Correction of Cardiac MRI Motion Artefacts During Reconstruction from k-space
Regional Multi-View Learning for Cardiac Motion Analysis: Application to Identification of Dilated Cardiomyopathy Patients
Fully automated myocardial strain estimation from cine MRI using convolutional neural networks
A multimodal spatiotemporal cardiac motion atlas from MR and ultrasound data