Regulation of 3D Cell Migration by Microtubule-Dependent Processes. The overarching aim of this research is to elucidate the molecular mechanisms that cells use to move in 3D environments: a basic biological function essential to development and homeostasis. During these processes, cells interact with their surroundings where they translate biophysical forces into biochemical signals to adapt their shape to move. This requires distinct signalling, controlled in space and time, to regulate the cr ....Regulation of 3D Cell Migration by Microtubule-Dependent Processes. The overarching aim of this research is to elucidate the molecular mechanisms that cells use to move in 3D environments: a basic biological function essential to development and homeostasis. During these processes, cells interact with their surroundings where they translate biophysical forces into biochemical signals to adapt their shape to move. This requires distinct signalling, controlled in space and time, to regulate the crosstalk between organelles and the cytoskeleton. To date, the role of microtubules remains elusive. Using interdisciplinary approaches combining advanced imaging technology with novel cell biology methods, the project aims to uncover fundamental knowledge about how cells interact with their environment.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101297
Funder
Australian Research Council
Funding Amount
$429,000.00
Summary
A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the e ....A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the emerging field of biological imaging and to deliver an integrated imaging platform for mapping various tissue microscopic components at the cellular level. Successful outcomes have the potential for commercialisation and will accelerate a range of fundamental science and engineering studies requiring imaging techniques.Read moreRead less
Ultra-fast serialised all optical image processing: addressing the electronic bottleneck in the world's fastest camera. Serial time encoded amplified microscopy can capture over a million frames per second. At this rate, a megapixel image would fill a terabyte hard disk in a second. We will use photonics to condense and manipulated the video stream so that only the important features are 'seen', making it practical to process and store on a computer.
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
Novel technologies for motion-compensated simultaneous Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) imaging. The aim of this work is to develop motion tracking and motion correction techniques for an emerging hybrid imaging technology, MR-PET. The MR-PET scanner simultaneously acquires structural MR images and functional PET images. The work will provide clearer images without the effects of motion blur for both research and clinical applications.
Imaging the foundation of the nervous system. This Project aims to understand the formation of the neural tube; a fundamental tissue structure that generates the brain and the spinal cord. Using interdisciplinary approaches and exploiting recent advances in transgenic and imaging technologies, the Project expects to reveal the complex interplay of molecular, cellular and mechanical processes that direct neural tissue formation and cell fate specification. Outcomes from the Project include knowle ....Imaging the foundation of the nervous system. This Project aims to understand the formation of the neural tube; a fundamental tissue structure that generates the brain and the spinal cord. Using interdisciplinary approaches and exploiting recent advances in transgenic and imaging technologies, the Project expects to reveal the complex interplay of molecular, cellular and mechanical processes that direct neural tissue formation and cell fate specification. Outcomes from the Project include knowledge of previously intractable developmental processes, training of future scientists and development of international collaborations. This should provide enhanced imaging capacity, a higher quality scientific workforce and position Australia at the forefront of developmental biology.
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Deep Weak Learning for Morphology Analysis of Micro and Nanoscale Images. This project will develop novel methods for automated discovery and quantification of image phenotypes from micro and nanoscale images. The outcome will be an advance of the state of the art in biomedical image analysis with a particular focus on generalized weakly-supervised deep learning models for morphological feature representation. The methodologies will transform the deep learning pipeline for real biomedical imagin ....Deep Weak Learning for Morphology Analysis of Micro and Nanoscale Images. This project will develop novel methods for automated discovery and quantification of image phenotypes from micro and nanoscale images. The outcome will be an advance of the state of the art in biomedical image analysis with a particular focus on generalized weakly-supervised deep learning models for morphological feature representation. The methodologies will transform the deep learning pipeline for real biomedical imaging scenarios with high heterogeneity and limited training data. The frameworks will facilitate high-throughput processing for a wide range of microscopy image modalities and biological applications, and potentially become the next generation computational platform to support fundamental research in human biology.Read moreRead less
Enhanced Through-Wall Imaging using Bayesian Compressive Sensing. The aim of this project is to develop radar imaging techniques which enable us to 'see' objects behind walls and opaque materials. The major intended breakthrough is the ability to image objects behind walls and inside buildings or enclosed structures without accessing the scene. Novel signal and image processing algorithms, based on Bayesian compressive sensing, will be developed to enhance image quality and resolution, improve s ....Enhanced Through-Wall Imaging using Bayesian Compressive Sensing. The aim of this project is to develop radar imaging techniques which enable us to 'see' objects behind walls and opaque materials. The major intended breakthrough is the ability to image objects behind walls and inside buildings or enclosed structures without accessing the scene. Novel signal and image processing algorithms, based on Bayesian compressive sensing, will be developed to enhance image quality and resolution, improve speed of operation, and reduce the cost and time of data acquisition and processing. Many applications are expected to benefit from this research including search and rescue, surveillance, security, and defence. The research outcomes are expected to enhance the capabilities of the Australian armed forces, counter-terrorism, police and law-enforcement agencies.Read moreRead less
Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emer ....Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emergency services. This new capability enhances utilisation of security resources to prevent injury and fatalities in evacuation scenarios, applicable to existing venues and influencing the development of new facilities around the country. The project delivers researcher training, global clientele for local technology and a platform for local industry growth.Read moreRead less