• Discovery and development of novel imaging biomarkers for clinical applications in the design of treatment strategies for various diseases
  • Assessment of high-precision quantitative and functional imaging methods to enable the design of clinical trials with reduced sample sizes or reduced follow-up
  • Development of requisite imaging acquisition protocols and image analysis tools appropriate to the design of new treatment strategies
  • Investigation of transformative, novel approaches guided by imaging that may lead to imaging-initiated minimally-invasive treatment methods
  • Application of AI algorithms and machine learning techniques (deep learning, U-net segmentation, contrastive learning, recurrent convolution neural network, YOLO, natural language processing) to advance image-initiated clinical decision support programs that would improve the quality and efficiency of clinical work to address workforce shortages and increase job satisfaction

Professor KT Bae

  • Body diffusion-weighted MR imaging (DW-MRI) − application in oncology, quantification of diffusion parameters and technique optimisation on 3T MRI
  • DW-MRI quantification beyond mono-exponential model
  • Qualitative and quantitative peritoneal imaging
  • Application of radiomics in gynaecological oncology

Dr EYP Lee

  • Stress cardiac magnetic resonance and perfusion mapping/quantification in
  • Asymptomatic high risk diabetics coronary microvascular disease and empagliflozin
  • CMR feature tracking for prognosis and diagnosis of diastolic dysfunction in heart failure with preserved ejection fraction and comparing this to catheter pressure measurements, echocardiography and CMR tagging
  • 4D flow in heart failure with preserved ejection fraction
  • Longitudinal study on CMR appearances of recovered COVID-19 patients, recovered viral respiratory infection patients, and post-vaccination patients
  • Coronary artery plaque changes imaged on CCT in patients on empagliflozin
  • Coronary artery volume and myocardial mass ratio for assessing coronary microvascular function imaged on CCT
  • CT Coronary calcium scoring in different ethnicities

Dr MY Ng

  • Deep-learning-based MRI reconstruction and quantification
  • Deep-learning-based medical imaging segmentation and classification
  • fMRI acquisition and modelling for brain function, BOLD and non-BOLD contrast mechanisms
  • MRI pulse sequence design and novel imaging contrasts
  • Molecular imaging, such as MR spectroscopy and chemical exchange saturation transfer
  • MRI hardware development

Dr P Cao

  • Using imaging for early detection, cancer characteristics, and response assessment
  • Nasopharyngeal carcinoma
  • Hepatocellular carcinoma
  • Prostate cancer
  • Quantitative radiomics and radiogenomics
  • Big data, machine learning, medical artificial intelligence
  • Deep learning imaging applications to ageing and longevity

Professor KT Bae

Dr VV Vardhanabhuti

  • Alzheimer's and other neurodegenerative diseases − volumetric MRI, functional MRI, MR perfusion, MR spectroscopy (MRS), amyloid and tau PET, susceptibility-weighted imaging (SWI), chemical exchange saturation transfer (CEST), artificial intelligence in dementia diagnosis
  • Demyelinating diseases, such as systemic lupus erythematosus, neuromyelitis optica and multiple sclerosis − arterial spin labelling (ASL), diffusion tensor imaging (DTI), MRS
  • Brain tumours − surrogate markers in anticancer drug trials using dynamic contrast enhanced (DCE) MR perfusion and MRS
  • Epilepsy − volumetric MRI, T1 Rho, MRI/PET
  • Stroke − MR perfusion (ASL) imaging in evaluation of stroke, MR vessel wall imaging in aneurysm, vasculitis and intracranial atherosclerosis, blood-brain-barrier imaging in haemorrhagic stroke, stroke imaging database in Hong Kong West Cluster of the Hospital Authority

Professor KT Bae

Dr HKF Mak

Find Out More

Information on selected projects or research areas: Interested candidates are advised to email the relevant supervisors.  Please enclose with your email: (i) your CV, (ii) a brief description of your research interest and experience, and (iii) two reference letters (reference letters not required for HKUMed UG students seeking MRes[Med] or URIS projects)

Research studies enquiries specific to the Department/School’s research should be directed to the Departmental Research Postgraduate Advisor: Dr P Cao ( caopeng1@hku.hk)

Information on the research programme, funding support and admission requirements could be found on the RPg Admissions website.

General admission enquiries should be directed to rpgmed@hku.hk.

Meet Our Students

SHI Jingjing

Place of Origin: China
Progress: PhD Year 3
Supervisor: Prof PL Khong




April 2021