Ultrafast tracking of physiological processes in the human eye. Recent developments in high-resolution imaging allow individual cells in the living eye to be studied at very high speeds. This project aims to explore a new class of scientific observations of rapid phenomena including: the capture and conversion of light energy to electrical energy, the spread of pressure waves through delicate networks of blood vessels, and fast eye movements used to navigate the visual scene. This project expect ....Ultrafast tracking of physiological processes in the human eye. Recent developments in high-resolution imaging allow individual cells in the living eye to be studied at very high speeds. This project aims to explore a new class of scientific observations of rapid phenomena including: the capture and conversion of light energy to electrical energy, the spread of pressure waves through delicate networks of blood vessels, and fast eye movements used to navigate the visual scene. This project expects to generate new knowledge about these processes using state of the art technology, to reveal more about how the eye and visual system work. Our novel measures of physiological function will offer significant future benefit in the early diagnosis and treatment of disorders occurring at the cellular level.Read moreRead less
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