Area of research
Radiology, Nuclear Medicine and Imaging · Computer Vision and Pattern Recognition
Research interest
Research interests include Medical Image Segmentation Techniques, Advanced MRI Techniques and Applications, Radiomics and Machine Learning in Medical Imaging, and Cardiac Imaging and Diagnostics.
Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge
Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study
Enhancing MR image segmentation with realistic adversarial data augmentation
MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images
Automated cardiovascular magnetic resonance image analysis with fully convolutional networks
Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation
A supervised learning approach for the robust detection of heart beat in plethysmographic data
Myocardial Perfusion: Near-automated Evaluation from Contrast-enhanced MR Images Obtained at Rest and during Vasodilator Stress