Research Projects
Deep Learning-Based Quantitative Assessment of White Matter Hyperintensity in Brain MRI

White matter hyperintensities (WMH) are common neuroimaging findings associated with various neurological conditions, including aging, stroke, and dementia. Accurate quantification of WMH burden is essential for diagnosis, prognosis, and treatment planning. Traditional assessment methods often rely on manual or semi-automated techniques, which can be time-consuming and subject to inter-observer variability. This project aims to develop advanced deep learning models to automate and improve the accuracy of WMH quantification using brain MRI data, particularly FLAIR images. Leveraging both publicly available datasets and our local data, the proposed models will be evaluated against conventional and baseline deep learning approaches. The ultimate goal is to streamline the WMH assessment process, making it more efficient and reliable, thereby supporting better clinical decision-making.

Professor J Huang, Department of Diagnostic Radiology

Professor Jianpan Huang is an Assistant Professor in the Department of Diagnostic Radiology at the Li Ka Shing Faculty of Medicine, The University of Hong Kong. He is also a junior fellow of the International Society for Magnetic Resonance in Medicine (ISMRM). His research interests encompass magnetic resonance imaging (MRI), chemical exchange saturation transfer (CEST) MRI, artificial intelligence in medical imaging, and neuroscience.

Professor Huang has published around 50 peer-reviewed articles in leading international journals, including Science Advances, Nature Communications, Magnetic Resonance in Medicine, and the IEEE Journal of Biomedical and Health Informatics, and holds eight authorized patents. He serves as a reviewer for numerous international scientific journals and funding agencies around the world. His research is supported by funding from the National Natural Science Foundation of China and the Research Grants Council of Hong Kong.

Biography
HKU Scholars Hub
Lab
ORCID
jphuang@hku.hk

For more information or to express interest for this project, please email the supervisor or the specified contact point in the project description.  Interested candidates are advised to enclose with your email:

1. your CV,
2. a brief description of your research interest and experience, and
3. two reference letters (not required for HKUMed UG students seeking MRes[Med]/URIS projects).

Information on the research programme, funding support and admission documentations could be referenced online at the Research Postgraduate Admissions website. General admission enquiries should be directed to rpgmed@hku.hk.

HKUMed MBBS students interested in the Master of Research in Medicine (MRes[Med]) programme may visit the programme website for more information.  

HKUMed UG students interested in the Undergraduate Research Internship Scheme (URIS) may visit the scheme’s website for more information.