Diamond Microneedles for Minimally Invasive Blood Collection. Blood sampling is a routine procedure for medical purposes to determine the physiological and biochemical status of patients. The aim of this project is to develop a reliable microneedle array for a blood collection procedures. Micro-scale needles for low-volume perforated blood samples are highly desirable due to its minimal invasiveness and painlessness. The miniaturization of sampling platforms driven by microneedles has the poten ....Diamond Microneedles for Minimally Invasive Blood Collection. Blood sampling is a routine procedure for medical purposes to determine the physiological and biochemical status of patients. The aim of this project is to develop a reliable microneedle array for a blood collection procedures. Micro-scale needles for low-volume perforated blood samples are highly desirable due to its minimal invasiveness and painlessness. The miniaturization of sampling platforms driven by microneedles has the potential to shift disease diagnosis and monitoring closer to the point of care. Expected outcomes include the development of synthetic diamond-based microneedles for the potential to greatly benefit society through improved and affordable healthcare and the development of new high-tech industries.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC170100035
Funder
Australian Research Council
Funding Amount
$4,743,710.00
Summary
ARC Training Centre for Innovation in Biomedical Imaging Technology. The ARC Training Centre for Innovation in Biomedical Imaging Technology expects to train 20 industry-ready innovation scientists who will undertake industry-driven research in the development and application of novel diagnostics, therapeutics and theranostics. They will inform changes in regulatory policy that support industry growth. The Centre will build multidisciplinary links between researchers and within industry to devel ....ARC Training Centre for Innovation in Biomedical Imaging Technology. The ARC Training Centre for Innovation in Biomedical Imaging Technology expects to train 20 industry-ready innovation scientists who will undertake industry-driven research in the development and application of novel diagnostics, therapeutics and theranostics. They will inform changes in regulatory policy that support industry growth. The Centre will build multidisciplinary links between researchers and within industry to develop ‘smart’ probes and ‘smart’ scanning, harnessing the digital revolution for better, cost effective diagnostic imaging and improved health outcomes.Read moreRead less
Insight from Darkness: Nanophotonics for real-time phase imaging. This project aims to develop ultrathin surfaces patterned on the nanoscale for extracting information from optical wavefields. These devices can be designed to provide real-time phase contrast imaging of transparent objects. This capability would open up the possibility of live-cell imaging with no expensive optical components and no, or minimal, computational post-processing. The planar configuration is designed to be compatible ....Insight from Darkness: Nanophotonics for real-time phase imaging. This project aims to develop ultrathin surfaces patterned on the nanoscale for extracting information from optical wavefields. These devices can be designed to provide real-time phase contrast imaging of transparent objects. This capability would open up the possibility of live-cell imaging with no expensive optical components and no, or minimal, computational post-processing. The planar configuration is designed to be compatible with next-generation lab-on-a-chip technologies and permit rapid throughput diagnostics with potential applications in biomedicine and materials science. Expected project outcomes may also underpin fundamental advances in understanding the interaction of light with nanostructures.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