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
Integrative brain imaging technologies. This project aims to develop quantitative metabolic imaging using simultaneous magnetic resonance imaging (MRI) and positron emission tomography (PET). The current generation of MR-PET scanners are capable of simultaneously acquiring MRI and PET data to enable quantitative anatomical, physiological and metabolic imaging. The project aims to develop new MRI methods for quantitative anatomical mapping, MR-based motion correction of dynamic PET scan data, and ....Integrative brain imaging technologies. This project aims to develop quantitative metabolic imaging using simultaneous magnetic resonance imaging (MRI) and positron emission tomography (PET). The current generation of MR-PET scanners are capable of simultaneously acquiring MRI and PET data to enable quantitative anatomical, physiological and metabolic imaging. The project aims to develop new MRI methods for quantitative anatomical mapping, MR-based motion correction of dynamic PET scan data, and joint estimation of physiological and metabolic organ activity. These advances will create innovative imaging technologies for advanced biomedical imaging research with a particular emphasis in healthy ageing.
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