In Biomedical Image Analysis (BioMedIA) Laboratory at Department of Computational and Data Sciences (CDS), our aim is to develop innovative AI-based methods for computational analysis of multidisciplinary biomedical images for clinical applications. We specifically focus on building scalable and translatable tools for big data applications in neuroimaging. We are also interested in tackling key challenges of medical image analysis including label scarcity and data diversity, model generalisability and interpretability.
Our current research areas include computer vision and machine learning-based methods for identification of MR imaging biomarkers for various neurological diseases, semi-supervised techniques for analysis of various imaging modalities, data harmonisation/domain adaptation, image reconstruction and quality improvement.
Information on ongoing research projects can be found here.