Despite a half-century of advancements, global MRI accessibility remains limited, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using permanent 0.05 Tesla magnets and deep learning for electromagnetic interference elimination, we developed highly simplified 0.05 Tesla MRI systems that operate using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging both brain (Nature Communications 2021) and various anatomical structures at whole-body level (Science 2024). Furthermore, we developed three-dimensional deep learning reconstruction methodologies to boost image quality by harnessing extensive high-field MRI data (MRM 2023, Science Advances 2023, Science 2024). We hope these advances will eventually lead to a new class of affordable and computing–powered ultra-low-field MRI scanners for point-of-care applications, addressing unmet clinical needs in diverse health care settings.
Professor Ed Xuekui Wu is Chair Professor of Biomedical Engineering and holds Lam Woo Professorship in Biomedical Engineering. He joined the University of Hong Kong Department of Electrical and Electronic Engineering in 2003. Before joining HKU, Professor Wu was an Associate Professor of Radiology and Biomedical Engineering at Columbia University in New York where he led the NMR Microimaging Laboratory. From 1990 to 1998, Professor Wu was the lead technical member in development of the world first 3D positron emission tomography (PET) system and an ultrahigh field magnetic resonance imaging (MRI) system at Columbia University. At present, Professor Wu is the founding Director of the interdisciplinary Laboratory of Biomedical Imaging and Signal Processing, and Research Director of 3T MRI Unit at HKU. He served as the Program Director of Medical Engineering Program from 2009 to 2013 and Associate Dean (Research) of HKU Faculty of Engineering from 2013 to 2016. His current research encompasses (1) MRI physics, data acquisition and image reconstruction algorithms through intelligent computing, and MRI system engineering for accessible healthcare; and (2) study of large-scale brain circuits and functions through high-field functional MRI, NMR diffusion and spectroscopy, optogenetic modulation, electrophysiology, behavioural assessment, and modelling.
Clean water and clean air are vital for public health. This project focuses on developing high-efficiency and environmentally sustainable filters for removing harmful air/water pollutants. The team has developed novel architectures and functionalities for the filters to achieve high permeance, high removal efficiency, and excellent reusability.
