Automatic cartilage segmentation in magnetic resonance imaging. Osteoarthritis (OA) is the most common form of arthritis, affecting nearly 1.4 million Australians. This research aims at engineering new tools for use in Magnetic Resonance Imaging systems to enable automated analyses of the cartilage and bones in joint images. The goals of the work are to assist with improved diagnosis and treatment planning for both chronic disease, such as OA, and acute injuries, such as cartilage and ligament ....Automatic cartilage segmentation in magnetic resonance imaging. Osteoarthritis (OA) is the most common form of arthritis, affecting nearly 1.4 million Australians. This research aims at engineering new tools for use in Magnetic Resonance Imaging systems to enable automated analyses of the cartilage and bones in joint images. The goals of the work are to assist with improved diagnosis and treatment planning for both chronic disease, such as OA, and acute injuries, such as cartilage and ligament tears in sporting injuries and other traumas.
The software developed will be provided on the project’s partner (Siemens) platform and will therefore be available worldwide and have a consequently large impact on the field.
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Automated Vector Extraction from Airborne Laser Scan Data. This project considers the problem of automatically extracting and vectorising the outlines of objects from Airborne Laser Scanning (ALS) data. The industry partner, AAM GeoScan, is a leading user of ALS systems in Australia, and has a need to develop automated solutions to this problem. ALS data is typically a dense cloud of 3D point data which represents the local terrain, as well as any trees, buildings or vehicles which may be in t ....Automated Vector Extraction from Airborne Laser Scan Data. This project considers the problem of automatically extracting and vectorising the outlines of objects from Airborne Laser Scanning (ALS) data. The industry partner, AAM GeoScan, is a leading user of ALS systems in Australia, and has a need to develop automated solutions to this problem. ALS data is typically a dense cloud of 3D point data which represents the local terrain, as well as any trees, buildings or vehicles which may be in the field of view. Spatial data is a very important resource, widely used in many types of urban and rural planning operations. Planning software packages require vectorised descriptions of building outlines and other spatial data, however this is not presently available from raw ALS data. The project will investigate this problem and develop new and effective means for producing it automatically from raw ALS data. Expected outcomes include a successful research masters studentship, the development of novel solutions to the problem which are directly applicable to the industry partner's core business, peer reviewed publications, and an strengthened link between the universities and the industry partner.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
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
Design of new two-dimensional materials for lithium sulphur batteries. Design of new two-dimensional materials for lithium sulphur batteries. This project aims to develop classes of electrode material systems for high performance batteries. This project will design new hierarchical cathode composites for a high capacity lithium-sulphur battery with a long cycling life. It intends to improve energy density by confining active sulphur in conductive graphene and exfoliated titanium dioxide nanoshee ....Design of new two-dimensional materials for lithium sulphur batteries. Design of new two-dimensional materials for lithium sulphur batteries. This project aims to develop classes of electrode material systems for high performance batteries. This project will design new hierarchical cathode composites for a high capacity lithium-sulphur battery with a long cycling life. It intends to improve energy density by confining active sulphur in conductive graphene and exfoliated titanium dioxide nanosheets, and use a unique hybrid protecting layer to suppress cycling instability. This research is expected to establish the relationship between synthetic conditions, structure, and electrochemical performance.Read moreRead less
Progressive Transmission of Street Directory Assistance and Business Pages over 3G and 4G mobile networks. Multimedia on-demand and live services over 3G and 4G mobiles will be enhanced. New methods for low volume, high information transfer multimedia transactions will be developed. This will create new jobs in the Information and Communication Technologies (ICT) sector. Progressive transmission of street directory assistance and business pages information to mobile handsets will enable citize ....Progressive Transmission of Street Directory Assistance and Business Pages over 3G and 4G mobile networks. Multimedia on-demand and live services over 3G and 4G mobiles will be enhanced. New methods for low volume, high information transfer multimedia transactions will be developed. This will create new jobs in the Information and Communication Technologies (ICT) sector. Progressive transmission of street directory assistance and business pages information to mobile handsets will enable citizens to make efficient use of their time and improve productivity. The 3G and 4G cellular telephone network, extended with 'mobile' base stations and satellite links, are especially attractive to a large country like Australia. Interactive information retrieval will become more universal and not limited through wired Internet connections.
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Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Reconfigurable System-on-Chip for Computer Network Appliances. As Internet connectivity becomes ubiquitous, so does the need for computer network security. As algorithms become more sophisticated, and network speeds increase, software-only implementations of network security applications become less feasible on small, embedded network appliances. This project investigates new computer architectures, based on reconfigurable System-on-Chip technology, which can improve algorithm speed through sp ....Reconfigurable System-on-Chip for Computer Network Appliances. As Internet connectivity becomes ubiquitous, so does the need for computer network security. As algorithms become more sophisticated, and network speeds increase, software-only implementations of network security applications become less feasible on small, embedded network appliances. This project investigates new computer architectures, based on reconfigurable System-on-Chip technology, which can improve algorithm speed through specialised instruction sets, hardware accelerators, and parallel processing. Research outcomes will be commercialised by the project's industry partner - a global leader in low-cost network security appliances.Read moreRead less
A generic decision-making design environment to enable end users in rural industries to develop expert systems. Successful decision support systems developed by end-users has been limited: our proposed approach advances this capability. Using natural representations of industry knowledge, this project will specify a generic design environment in which industry end-users can develop relevant decision support systems. It extends expert systems technologies to overcome known limitations, increasin ....A generic decision-making design environment to enable end users in rural industries to develop expert systems. Successful decision support systems developed by end-users has been limited: our proposed approach advances this capability. Using natural representations of industry knowledge, this project will specify a generic design environment in which industry end-users can develop relevant decision support systems. It extends expert systems technologies to overcome known limitations, increasing context and relevance and encouraging user uptake. Key industry stakeholders will select relevant problems to identify decision categories, leading to specification of the generic design environment. This promises improved decision quality for dairy farmers in the recently deregulated dairy industry; the design environment will be transferable to other rural industries.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