Our projects
Our research group is dedicated to the use of computational modelling and AI to characterise “fingerprints” of brain tumours and other diseases of neurological/neurosurgical interest to develop automated diagnosis in neuroimaging and neuropathology. We develop and validate algorithms to develop new computational methods aimed to help clinicians and surgeons in differential diagnosis and decision-making. The long-term aim is to implement the use of the computerised analysis tools to aid surgeon-Multidisciplinary Team(MDT)-based judgment, to improve diagnostic power, to reduce errors in evaluations of radiological images, and as a result, improve the treatment and outcome of patients affected by brain tumours and other diseases.
- Analysis of the spectroscopic fingerprinting of brain tumours. We introduced for the first time in Australia the use of 2HG-MRS for detection of genetic mutations (IDH) in gliomas. We are currently working on developing further the concept of “spectrobiopsy”
- Computational fractal- and AI-based analysis of intra-tumoural features, such as SWI patterns in MR imaging
- Features extractions and pattern recognition in brain tumours, radiological mimics of brain tumours and cerebrovascular diseases (including aneurysms and arteriovenous malformations)
- Computational analysis of neuroimaging (including MRI and PET) of the brain in all its physiopathological spectrum, neuropathology slides, neurophysiological time-series, and neuroanatomy images
- Automatic segmentation, typing and grading of brain tumours in neuroimaging
- Integration of neuroanatomy lab with advanced computational modelling
- Advanced neuroanatomy/neuroimaging rendering
- Connectomics in brain tumours
- Connectomics & Proteomics in pain neuromodulation
- Fluorescence-guided neurosurgery and Machine Learning
- Deep learning in videoendoscopy
- MEG in neurosurgery and cognitive neuroscience
- Machine Vision and Eye Tracking
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