Machine Assisted, Multi-scale Spatial and Temporal Observation and Modeling of Marine Benthic Habitats. The Integrated Marine Observing System (IMOS) science plans include sampling campaigns reliant on Autonomous Underwater Vehicle (AUV) Facility data and designed to address the issues of marine biodiversity quantification and assurance. The proposed research will directly enhance the effectiveness of these programs by speeding labour-intensive analyses, aggregating the results, and searching f ....Machine Assisted, Multi-scale Spatial and Temporal Observation and Modeling of Marine Benthic Habitats. The Integrated Marine Observing System (IMOS) science plans include sampling campaigns reliant on Autonomous Underwater Vehicle (AUV) Facility data and designed to address the issues of marine biodiversity quantification and assurance. The proposed research will directly enhance the effectiveness of these programs by speeding labour-intensive analyses, aggregating the results, and searching for ecological patterns on a national scale that would be difficult to identify using traditional approaches tuned to process-scale studies. Australian society stands to benefit by virtue of improved large-scale models of ecosystem function and reduced cost for conducting marine ecosystem investigations.Read moreRead less
Special Research Initiatives - Grant ID: SR0354734
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
The Australian Research Network for Medical Devices: advanced technology solutions for patients and practitioners. Medical Device technologies embrace a wide range of scientific, engineering and medical knowledge, with the goal of assisting a clinical professional (doctor or nurse) deliver a service to a patient in an efficacious, cost effective manner. Development of appropriate medical devices, whether for diagnosis, treatment or prevention of disease or disability, is critical to improving h ....The Australian Research Network for Medical Devices: advanced technology solutions for patients and practitioners. Medical Device technologies embrace a wide range of scientific, engineering and medical knowledge, with the goal of assisting a clinical professional (doctor or nurse) deliver a service to a patient in an efficacious, cost effective manner. Development of appropriate medical devices, whether for diagnosis, treatment or prevention of disease or disability, is critical to improving health care and reducing health care costs. To be successful, a device must include all relevant disciplines in the research, development and testing phases. This network will bring together these groups, promoting knowledge sharing and cross-disciplinary investigations that illuminate current device limitations and potential solutions.Read moreRead less
Special Research Initiatives - Grant ID: SR0567334
Funder
Australian Research Council
Funding Amount
$125,748.00
Summary
A Grid-Enabled National Archive of Nanostructural Imagery (GRANI). The Nanostructural Analysis Network Organization (NANO) is an Australian Major National Research Facility that provides access to a grid of advanced microscopic instruments for the nanostructural analysis of both physical materials and biological systems. The aim of this initiative is to provide the NANO community with a set of common, interoperable tools and services to enable more efficient, cost-effective storage, management, ....A Grid-Enabled National Archive of Nanostructural Imagery (GRANI). The Nanostructural Analysis Network Organization (NANO) is an Australian Major National Research Facility that provides access to a grid of advanced microscopic instruments for the nanostructural analysis of both physical materials and biological systems. The aim of this initiative is to provide the NANO community with a set of common, interoperable tools and services to enable more efficient, cost-effective storage, management, analysis and sharing of generated microscopic images, video and analytical data. The significance of the proposed middleware is that it will improve collaboration and reduce duplication across many disciplines, through a shareable, distributed national scientific image/video database.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
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
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
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
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
The worlds next door: terrestrial exoplanets with the TOLIMAN space mission. This project aims to to explore our nearest neighbour star system, Alpha Centauri, for the first time probing for exoplanets with physical characteristics that resemble those of Earth. The finding of any such world, with the potential to support a biosphere like our own and lying only 4 light-years away, would profoundly alter our view of our place in the universe. The primary outcome of this project will be the design, ....The worlds next door: terrestrial exoplanets with the TOLIMAN space mission. This project aims to to explore our nearest neighbour star system, Alpha Centauri, for the first time probing for exoplanets with physical characteristics that resemble those of Earth. The finding of any such world, with the potential to support a biosphere like our own and lying only 4 light-years away, would profoundly alter our view of our place in the universe. The primary outcome of this project will be the design, construction, launch and operation of a novel and innovative space telescope: the TOLIMAN mission. This profoundly benefits the Australian space and university sectors, partnering them with international agencies to deliver marquee science with global impact: the search for our first stepping stone to interstellar space.Read moreRead less
Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global com ....Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global competitiveness. Expected outcomes of this project will help to break the communication barriers between the Deaf and hearing population. This should provide significant benefits to Deaf communities through enhanced communication and improved quality-of-life, leading to a fair, more inclusive and resilient Australian society.Read moreRead less