Hao Li
DPhil Student
I am a DPhil candidate working at the FMRIB Physics Group under the supervision of Prof Thomas Okell, Prof Peter Jezzard, and Prof Mark Chiew, as well as Dr Iulius Dragonu from Siemens Healthineers. My research focuses on developing novel image reconstruction methods for highly accelerated magnetic resonance angiography (MRA) of the in vivo human brain using deep learning.
I obtained my MEng in Biomedical Engineering from Imperial College London. During my undergraduate studies, I worked as a research intern at Imperial’s National Heart and Lung Institute with Dr Guang Yang on developing deep learning-based methods for advanced MRI image processing and analysis.
My DPhil study is fully funded by the Medical Research Council, the Nuffield Department of Clinical Neurosciences, and Siemens Healthineers through an Oxford-MRC DTP iCASE studentship.
Recent publications
Few-shot learning for highly accelerated 3D time-of-flight MRA reconstruction.
Journal article
Li H. et al, (2026), Magn Reson Med, 95, 770 - 786
Few-shot learning for highly accelerated 3D time-of-flight MRA reconstruction
Preprint
Li H. et al, (2025)
Large-Kernel Attention for 3D Medical Image Segmentation.
Journal article
Li H. et al, (2024), Cognit Comput, 16, 2063 - 2077
Region-based evidential deep learning to quantify uncertainty and improve robustness of brain tumor segmentation.
Journal article
Li H. et al, (2023), Neural Comput Appl, 35, 22071 - 22085
Human treelike tubular structure segmentation: A comprehensive review and future perspectives.
Journal article
Li H. et al, (2022), Comput Biol Med, 151