Computational neuroanatomy is about a comprehensive structural and functional model of the brain. The distribution of structural changes of human brain reflects the underlying pathology. The increasing sophistication of MRI allows neuroanatomical structures to be visualized in vivo in unprecedented detail. Clinical MRI is able to give good soft-tissue contrast and high spatial (<1 mm) resolution. Due to rapid advances in computing power and algorithm development, we are now well placed to study the extraordinary MRI-visible morphological variability of the human brain through mathematical models sensitive to subtle changes in neuroanatomical shape, complexity and tissue characteristics. One of the key requirements of neuroimaging research is the multi-disciplinary collaborations between neuroscience, engineering and medicine and a host of sub-disciplines. While the research subjects and the clinical needs are provided by medicine, the theoretical underpinnings come from mathematics and statistics, and the methodological approaches from computer science and biomedical engineering, all forming critical components of the enterprise. Our recent work includes mapping and modeling of cerebral white matter hyperintensities, algorithm development for examining the shapes and sizes of brain structures and cortical atrophy. fMRI, pMRI, MRS, and PET are also currently being used as brain imaging modalities in various studies.
Broad Research Areas:
Neurosciences, Brain Ageing, NeuroImaging / Neuro-radiology, Medical Informatics, Pattern Recognition & Data Mining, Markov models
Ph.D. (Engineering, Sydney University)
Specific Research Keywords:
Computational neuroanatomy, Brain Anatomy, MRI, Mathematical Modelling, Medical Imaging