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
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
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