Biophysics-informed deep learning framework for magnetic resonance imaging. This project aims to bring about a paradigm shift from the conventional non-quantitative magnetic resonance imaging to ultra-fast, quantitative, and artefact free imaging. This project integrates biophysics and artificial intelligence, and it is expected to bring new knowledge in both fields. The expected outcomes of this project include next generation magnetic resonance imaging methods with a fundamental shift in the ....Biophysics-informed deep learning framework for magnetic resonance imaging. This project aims to bring about a paradigm shift from the conventional non-quantitative magnetic resonance imaging to ultra-fast, quantitative, and artefact free imaging. This project integrates biophysics and artificial intelligence, and it is expected to bring new knowledge in both fields. The expected outcomes of this project include next generation magnetic resonance imaging methods with a fundamental shift in the approach to image artefacts and image quantification. This project is expected to advance both single subject and population level biomedical imaging with greater accuracy and cost-effectiveness. This project also promotes explainable and generalisable artificial intelligence in medical imaging.Read moreRead less
Towards direct imaging of neuronal currents with MRI. This project aims to develop novel neuronal current magnetic resonance imaging (nc-MRI) methods that harness the oscillatory behaviour of neuronal magnetic fields. Current methods of detecting neuronal activity in the living human brain have limited spatial and temporal resolution. Use of nc-MRI aims to overcome these limitations by imaging the effects on the MRI signal of small transient magnetic fields associated with neuronal activity. Sig ....Towards direct imaging of neuronal currents with MRI. This project aims to develop novel neuronal current magnetic resonance imaging (nc-MRI) methods that harness the oscillatory behaviour of neuronal magnetic fields. Current methods of detecting neuronal activity in the living human brain have limited spatial and temporal resolution. Use of nc-MRI aims to overcome these limitations by imaging the effects on the MRI signal of small transient magnetic fields associated with neuronal activity. Signal-to-noise ratio is at the limits of detectability using current imaging systems and nc-MRI is yet to be convincingly demonstrated. An integrated framework for simulating nc-MRI in the visual cortex is expected to be developed.Read moreRead less
The development and testing of a device to enhance the application of repetitive transcranial magnetic stimulation. This project aims to develop and evaluate a new device designed to substantially enhance the use of transcranial magnetic stimulation, a technology, which is increasingly being applied in the treatment of disorders such as depression, as well as in the study of normal and abnormal brain function.