Sampling and processing for diffusion magnetic resonance imaging. This project aims to develop optimal, efficient and robust signal processing methods for diffusion magnetic resonance imaging (dMRI) with reduced scan times. A child, possibly distressed, can only be motionless long enough to undergo a basic dMRI scan of the brain, but enhanced forms of dMRI need at least 60 minutes. The project’s processing methods will use spherical geometries, which encode information about white matter fibres ....Sampling and processing for diffusion magnetic resonance imaging. This project aims to develop optimal, efficient and robust signal processing methods for diffusion magnetic resonance imaging (dMRI) with reduced scan times. A child, possibly distressed, can only be motionless long enough to undergo a basic dMRI scan of the brain, but enhanced forms of dMRI need at least 60 minutes. The project’s processing methods will use spherical geometries, which encode information about white matter fibres in the brain, to collect and reconstruct images. The project is expected to reduce dMRI scan times and ultimately make non-invasive and inexpensive early detection of neurological disorders such as dementia feasible.Read moreRead less
Novel time-frequency techniques for analysing and modeling non-stationary physical and engineering data. This project addresses an issue of fundamental importance in science and technology, where non-stationary data (which have time-varying statistics) are ubiquitous. Therefore, the development of time-frequency tools to model and analyse non-stationary data has great potential for impact in a wide range of areas reaching from seismic data analysis to biomedical signal processing to sonar and ra ....Novel time-frequency techniques for analysing and modeling non-stationary physical and engineering data. This project addresses an issue of fundamental importance in science and technology, where non-stationary data (which have time-varying statistics) are ubiquitous. Therefore, the development of time-frequency tools to model and analyse non-stationary data has great potential for impact in a wide range of areas reaching from seismic data analysis to biomedical signal processing to sonar and radar. Employing techniques to be developed in this proposal, we expect to be able to classify and detect features of non-stationary data that were unrecognisable using hitherto known methods.Read moreRead less
Spectral analysis with selective harmonic emphasis. This project lies under ARC research priority area "Frontier Technologies for Building and Transforming Australian Industries". The signal processing algorithms to be developed in this project will be useful in many important practical applications, which include various bio-medical imaging modalities, beamforming, radar, sonar and target tracking using sensor arrays. The idea is to use the prior knowledge to enhance certain desired properties ....Spectral analysis with selective harmonic emphasis. This project lies under ARC research priority area "Frontier Technologies for Building and Transforming Australian Industries". The signal processing algorithms to be developed in this project will be useful in many important practical applications, which include various bio-medical imaging modalities, beamforming, radar, sonar and target tracking using sensor arrays. The idea is to use the prior knowledge to enhance certain desired properties of the algorithms via intelligent processing. In this light the project also lies within the ARC research priority area of "Smart Information use".Read moreRead less
Advanced biosensing in the terahertz (THz) sub-wavelength regime. This project will build on Australian excellence in photonics, exploiting the advanced use of T-rays for sensing of biological substances such as proteins and DNA. For the first time, this will enable contactless automated sensing for high-speed medical screening of diseases, a critical step toward the ultimate vision of customised medicine.
Continuous wave excitation for low power Magnetic Resonance Imaging. This project aims to augment the capabilities of Magnetic Resonance Imaging (MRI) systems, using continuous wave (CW) transmission and signal reception, to image objects using very low excitation power. Any given MRI sequence tries to solve an inverse problem, involving estimation of some subset of hidden states and parameters of the system, given the observed data. Using transient and steady-state CW magnetisation dynamics to ....Continuous wave excitation for low power Magnetic Resonance Imaging. This project aims to augment the capabilities of Magnetic Resonance Imaging (MRI) systems, using continuous wave (CW) transmission and signal reception, to image objects using very low excitation power. Any given MRI sequence tries to solve an inverse problem, involving estimation of some subset of hidden states and parameters of the system, given the observed data. Using transient and steady-state CW magnetisation dynamics to solve inverse problems is expected to advance technology toward lower power, lower cost solutions for MRI scanners in healthcare and industrial applications, including materials science and mineral processing.Read moreRead less
Signal processing algorithms for interpreting multi-dimensional ambulatory data during normal activities: correlates of current measures of fall risk. This project will develop algorithms to analyse human movement, measured using a small waist-worn sensor, which approximate existing clinical tests to identify likely fallers. This will enable future fall risk monitor development. This is an important problem as one in three senior citizens fall each year, costing around $500 million in healthcare ....Signal processing algorithms for interpreting multi-dimensional ambulatory data during normal activities: correlates of current measures of fall risk. This project will develop algorithms to analyse human movement, measured using a small waist-worn sensor, which approximate existing clinical tests to identify likely fallers. This will enable future fall risk monitor development. This is an important problem as one in three senior citizens fall each year, costing around $500 million in healthcare.Read moreRead less
Advanced Signal Processing for Radiation Spectroscopy. Southern Innovation develops and markets world-leading pulse processing technologies for the rapid, accurate detection and measurement of radiation. The underlying real-time signal processing challenge relates to isolating often overlapping pulses, determining when each pulse arrived and the energy of each pulse. Recent advances in the computational power of digital signal processing boards makes it timely to develop innovative pulse process ....Advanced Signal Processing for Radiation Spectroscopy. Southern Innovation develops and markets world-leading pulse processing technologies for the rapid, accurate detection and measurement of radiation. The underlying real-time signal processing challenge relates to isolating often overlapping pulses, determining when each pulse arrived and the energy of each pulse. Recent advances in the computational power of digital signal processing boards makes it timely to develop innovative pulse processing algorithms based on optimal filtering of stochastic processes. It is expected that these algorithms will have widespread impact, both commercially for minerals exploration, materials analysis, medical imaging and security screening, and scientifically for improving the performance of synchrotrons and other equipment.Read moreRead less
Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed ....Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed methodology enables quantification of confidence in the predictions. This will provide ship owners, directly to their vessels and/or at the fleet management centres, information such as weather reports, reliable collision/no-collision warnings and avoidance strategies, on-the-fly. Read moreRead less
Optimisation of signal processing and electrical stimulation algorithms for the abatement of epileptic seizures. Epilepsy is the second-most common neurological disorder behind stroke and ischemic attacks, affecting 1-2 per cent of the nation's population. Pharmaceutical therapies are ineffective in approximately one third of cases, the result being a large unmet need for novel treatments. The devices to be produced through this project will improve the quality of life of many patients in the fu ....Optimisation of signal processing and electrical stimulation algorithms for the abatement of epileptic seizures. Epilepsy is the second-most common neurological disorder behind stroke and ischemic attacks, affecting 1-2 per cent of the nation's population. Pharmaceutical therapies are ineffective in approximately one third of cases, the result being a large unmet need for novel treatments. The devices to be produced through this project will improve the quality of life of many patients in the future and alleviate their dependence on traditional medications. The devices will also reduce the patients' requirements for medical practitioners, hospital and ambulance services, and will therefore also reduce the financial burden that neurological and epilepsy patients place on the community.Read moreRead less
Low Loss Distributed Wind Generators with Reduced Electromagnetic Interference and Shaft Voltage Based on Multilevel Converters. Distributed wind generators with minimum electromagnetic interference and bearing spikes are very important for the Australian energy industry because they are an environmentally friendly energy source. Predicting and reducing electromagnetic interferences and mechanical failures in wind farm systems is an important issue especially for the next generation of wind sys ....Low Loss Distributed Wind Generators with Reduced Electromagnetic Interference and Shaft Voltage Based on Multilevel Converters. Distributed wind generators with minimum electromagnetic interference and bearing spikes are very important for the Australian energy industry because they are an environmentally friendly energy source. Predicting and reducing electromagnetic interferences and mechanical failures in wind farm systems is an important issue especially for the next generation of wind systems when fast and advanced power electronic switches can create more EMI noise for both onshore and offshore wind farms. Medium-Voltage Direct Current (MVDC) systems have good performance and low losses, and are of particular interest to states which are close to wind power sources.Read moreRead less