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
Multi-modal, Multi-dimensional Virtual Microscopy for Diagnostic Quantitative Pathology. This project will contribute to the development of a new generation of virtual microscopy (VM) systems that provide new and innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of pathology. These systems have the potential to significantly enhance the efficiency and efficacy of not only primary diagnostic workflows, but also aspects of profi ....Multi-modal, Multi-dimensional Virtual Microscopy for Diagnostic Quantitative Pathology. This project will contribute to the development of a new generation of virtual microscopy (VM) systems that provide new and innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of pathology. These systems have the potential to significantly enhance the efficiency and efficacy of not only primary diagnostic workflows, but also aspects of proficiency testing and continuing education vital for a vibrant, well regulated discipline. In addition, the project will contribute to our knowledge of the pathology assessed in the screening and diagnosis of cancers such as cervical, lung and bladder cancers.Read moreRead less
A Phase III Trial Comparing Adjuvant Versus Salvage Radiotherapy For High Risk Patients Post Radical Prostatectomy
Funder
National Health and Medical Research Council
Funding Amount
$819,138.00
Summary
About half of all patients Treated with an operation to remove their prostate cancer have a high chance of the cancer coming back. Giving immediate radiotherapy to all patients will improve cure rates but does not benefit all men and can cause significant side effects. This study explores whether it is safe to wait and only give radiotherapy when there is a rising PSA after surgery indicating active cancer. A total of 470 men from Australasia will enter this study comparing the two approaches.
Dynamics of Causal Knowledge. We operate in complex dynamic environments including highly sensitive and safety-critical situations such as medical emergencies, disaster management and air-traffic control systems. Our knowledge of what causes what plays a pivotal role in making correct decisions in such situations. To ensure robustness and sound behaviour of the underlying causal knowledge systems, their designs and implementations must be formally well grounded. This is an important but difficul ....Dynamics of Causal Knowledge. We operate in complex dynamic environments including highly sensitive and safety-critical situations such as medical emergencies, disaster management and air-traffic control systems. Our knowledge of what causes what plays a pivotal role in making correct decisions in such situations. To ensure robustness and sound behaviour of the underlying causal knowledge systems, their designs and implementations must be formally well grounded. This is an important but difficult challenge. This project aims to systematically develop a logic-based framework to adequately capture and reason about evolving causal knowledge. This research is expected to form the basis for smart decision making, and be evaluated on practical applications.Read moreRead less
Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive ....Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive and specific detection of early cancers, the potential reductions in morbidity and mortality from breast cancer will be of immense value. Successful implementation of the proposed project will further enhance Australia's position as a world leader in biomedical research and application of computational technologies to health problems.Read moreRead less
Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising ap ....Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising approach, but its accuracy is far from satisfactory. The software systems developed in this project will be used in structural identification of target proteins in drug design. This will make drug design process more efficient, saving time and cost, potentially saving lives.Read moreRead less
Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the ....Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the early detection and warning of cyberbullying and approach open a new way to discover interaction patterns with a large number of participants over evolving and complex social networks.Read moreRead less
Sequencing and assembling microbial community metagenomes in real-time. This project aims to assemble metagenomes directly from environmental samples using nanopore sequencing. Short-read approaches to metagenomics cannot assemble mixed genomes from an environmental sample, so focus on describing which species and genes are present. Long-read nanopore sequencing enables the assembly of full genomes of multiple species in a sample. Assembling complete genomes in important resources such as water ....Sequencing and assembling microbial community metagenomes in real-time. This project aims to assemble metagenomes directly from environmental samples using nanopore sequencing. Short-read approaches to metagenomics cannot assemble mixed genomes from an environmental sample, so focus on describing which species and genes are present. Long-read nanopore sequencing enables the assembly of full genomes of multiple species in a sample. Assembling complete genomes in important resources such as water and soil should lead to deeper understanding of the dynamics, variation and transfer of genetic material within these resources’ microbial communities, strategies to manage microbial diversity, and improved productivity and long-term sustainability for these resources.Read moreRead less
Special Research Initiatives - Grant ID: SR0567196
Funder
Australian Research Council
Funding Amount
$55,000.00
Summary
Improved early detection of breast cancer enabled by grid-computing and advanced modelling and visualisation of MR images. This project will investigate the utility of grid computing in the detection of breast cancer from magnetic resonance (MR) images. The large quantity of data acquired using MR imaging is difficult for clinicians to review and the cost of missed or incorrect detection is high. To provide rapid visualisation and assessment of the acquired data, grid computing will be used in c ....Improved early detection of breast cancer enabled by grid-computing and advanced modelling and visualisation of MR images. This project will investigate the utility of grid computing in the detection of breast cancer from magnetic resonance (MR) images. The large quantity of data acquired using MR imaging is difficult for clinicians to review and the cost of missed or incorrect detection is high. To provide rapid visualisation and assessment of the acquired data, grid computing will be used in conjunction with interactive visualisation with haptic feedback. Grid computing experience and haptic device expertise will be achieved via Swedish collaborators. The successful outcome of this project will be software for the production of 3D colour-coded breast images in which suspicious regions are highlighted and can be physically interrogated using the haptic device.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less