Neurodevelopment and Plasticity
Our focus is on developing imaging techniques that provide enhanced information about neuropathology for improved detection and diagnosis leading to a better understanding of prognosis for neurodevelopmental disorders and brain trauma. We aim to use advances in neuroimaging to measure localisation and extent of neuroplasticity in response to evidence-based interventions..
Much of our focus is on Cerebral Palsy (CP), the most common physical disability in children (1 in 500 children affected) arising from a brain injury occurring before or around birth. The lifelong consequences inflict enormous personal and financial burden on both families and society – it is Australia’s 5th most expensive health condition. Advanced structural imaging, typically MRI, is performed to assess the extent of brain injury, and guide physical therapy. However, the quantitative link between injury and health outcomes for these conditions remains poorly understood. Although vast amounts of imaging data now exists to examine these conditions in detail and design optimal treatment regimens, current methods for quantifying injury have been limited by the inability to model severe pathology..
We have developed the first fully automated web based clinical support tool for paediatric brain injury, currently being evaluated both nationally and internationally with clinical collaborators. We have also developed an automated neonatal MRI outlier detection, interpolation and super-resolution image reconstruction for a specific neonatal dataset.
Team Leader, senior research scientist whose work predominantly centres on digital services for equitable healthcare through the development of technologies to assist with chronic illness, neurological conditions, ageing, genomic healthcare, mental health and well being for disadvantaged populations, Indigenous Australians and non English speaking patients.
Research scientist with a background in medical imaging (MRI & PET), neuroscience and biomedical informatics. He works on the AIBL and PISA projects in his role as an informatician. He also has a strong interest in the neuroscience of dementia, especially Alzheimer’s disease and on applying informatics tools and principals to do reproducible science and reuse data.
Postdoctoral Fellow, developing image processing algorithms using structural MRI that provide important biomarkers to assist clinicians in the diagnosis and treatment of several childhood neurological conditions, including Cerebral Palsy.
Research Assistant, working on data management for Medical and Clinical Imaging Teams, including the development and implementation of the bioinformatics platform and standard operating procedures (SOPs) for the team.
Postdoctoral Fellow, working on the application of deep learning/machine learning techniques on neonatal MRI for a very early prediction of Cerebral Palsy and later neurodevelopmental outcome.
Postdoctoral Fellow, developing a fully automated neurosurgical planning platform which incorporates information from structural MRI, advanced diffusion MRI, and advanced functional MRI.
Liza van Eijk
Visiting Scientist, working on extracting and validating measures of brain morphology and microstructure based on neonatal MRI, and examining whether these brain measures can be used as a biomarker to predict outcomes in infants born preterm (Postdoctoral Fellow at the Child Health Research Centre, Faculty of Medicine, the University of Queensland).
Research Scientist, developing methods for prediction of outcomes for preterm-born infants
Senior Research Scientist with experience in developing and and trialling novel interventions for improved physical and mental health outcomes in a range of clinical populations and ageing.