Breakthrough technologies in implantable bionics. This project aims to introduce revolutionary changes in implantable bionics via miniaturisation, automation and improved reliability and generating new knowledge by leveraging recent advances in laser processes. Expected outcomes include innovative hybrid thin-film/thick-film electrode arrays with more channels and charge-carrying capacity for neuromodulation; novel glass interfaces that facilitate deeply-miniaturised hermetic packages; and failu ....Breakthrough technologies in implantable bionics. This project aims to introduce revolutionary changes in implantable bionics via miniaturisation, automation and improved reliability and generating new knowledge by leveraging recent advances in laser processes. Expected outcomes include innovative hybrid thin-film/thick-film electrode arrays with more channels and charge-carrying capacity for neuromodulation; novel glass interfaces that facilitate deeply-miniaturised hermetic packages; and failure analysis to ensure study aims result in new processes that are as or more reliable than the current state-of-the-art. This work will create new and novel manufacturing processes, and trains the next generation of innovators equipped with the tools to advance implantable bionics into the future.Read moreRead less
Mid-Career Industry Fellowships - Grant ID: IM230100002
Funder
Australian Research Council
Funding Amount
$1,056,049.00
Summary
Artificial intelligence empowered multi-modal biomedical imaging. This Industry Fellowship aims to transform biomedical imaging using artificial intelligence with world-leading industry partners. The project expects to make a major advance in multi-modal Magnetic Resonance Imaging and Positron Emission Tomography image reconstruction for robust, accurate and efficient imaging. This project timely addresses industry needs with novel solutions and will establish a technology roadmap to inform and ....Artificial intelligence empowered multi-modal biomedical imaging. This Industry Fellowship aims to transform biomedical imaging using artificial intelligence with world-leading industry partners. The project expects to make a major advance in multi-modal Magnetic Resonance Imaging and Positron Emission Tomography image reconstruction for robust, accurate and efficient imaging. This project timely addresses industry needs with novel solutions and will establish a technology roadmap to inform and de-risk future research and development in image reconstruction. The project outcomes should provide benefits to Australians with cost-effective imaging and benefits to Australia's biomedical industry with well-aligned intellectual properties and training of future scientists with industry knowledge.Read moreRead less
A novel precision-engineered microfluidic chip for wear particle research. This project aims to develop 1- novel protocols to generate clinically-relevant wear particles from spinal implants in-vitro and 2- a technological framework for the fabrication of a novel microfluidic 3D spinal implant-on-a-chip with tailored mechanical, material and biological properties. This will provide a cost-effective tool, currently unavailable, that allows investigation into the impact of wear particles on health ....A novel precision-engineered microfluidic chip for wear particle research. This project aims to develop 1- novel protocols to generate clinically-relevant wear particles from spinal implants in-vitro and 2- a technological framework for the fabrication of a novel microfluidic 3D spinal implant-on-a-chip with tailored mechanical, material and biological properties. This will provide a cost-effective tool, currently unavailable, that allows investigation into the impact of wear particles on healthy spinal disc cells. We expect our technological framework to become an invaluable tool for biomedical engineers, biologists, and bio-engineers to work together and generate clinically relevant in-vitro data that supports optimisation for spinal implant design, fabrication, and safety. 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