Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0775747
Funder
Australian Research Council
Funding Amount
$160,000.00
Summary
Distributed Medical Image Analysis and Visualisation Engine (MedVis). Improved understanding of neurological processes is crucial to improving clinical outcomes for patients. MedVis will contribute in three ways: support development of new methods of interpretation and analysis of complex neurological studies, allowing current methods to be applied more efficiently, and enabling distributed simulations and visualisations in real-time from remote sites.
The leading-edge, grid-based, software and ....Distributed Medical Image Analysis and Visualisation Engine (MedVis). Improved understanding of neurological processes is crucial to improving clinical outcomes for patients. MedVis will contribute in three ways: support development of new methods of interpretation and analysis of complex neurological studies, allowing current methods to be applied more efficiently, and enabling distributed simulations and visualisations in real-time from remote sites.
The leading-edge, grid-based, software and computational techniques developed for the project will enable visualization, analysis and modelling of massive volumes of image and other visualisation data. This capability is important in medical research where large visualisation data volumes are being created and studied by experts remote from each other.
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Special Research Initiatives - Grant ID: SR0354604
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
ARC Network in Imaging Science and Technology. The ARC Network in Imaging Science and Technology is a field of research network covering the fundamental science and technological development of applied imaging systems. The network will encompass all aspects of the imaging sciences from image formation, through image processing and analysis, and on to image visualisation. In particular, the network will focus on a number of application areas that utilise these core technologies: medical imaging; ....ARC Network in Imaging Science and Technology. The ARC Network in Imaging Science and Technology is a field of research network covering the fundamental science and technological development of applied imaging systems. The network will encompass all aspects of the imaging sciences from image formation, through image processing and analysis, and on to image visualisation. In particular, the network will focus on a number of application areas that utilise these core technologies: medical imaging; surveillance and security; materials science and metallurgy; environmental monitoring; and consumer imaging. In this way, the network will provide an environment for creative inter-disciplinary research to the socio-economic benefit of Australia.Read moreRead less
Monitoring, Calibration and Control of a Micro Assembly Process with Machine Vision Systems. A machine vision system will be developed and applied to monitor, calibrate, and control a novel surgical product assembly process of microscale. The machine vision system will benchmark the volumetric information of the needles, calibrate the position of the components, and control the assembly procedures. The successful implementation of the system will assist the production of finer surgical product ....Monitoring, Calibration and Control of a Micro Assembly Process with Machine Vision Systems. A machine vision system will be developed and applied to monitor, calibrate, and control a novel surgical product assembly process of microscale. The machine vision system will benchmark the volumetric information of the needles, calibrate the position of the components, and control the assembly procedures. The successful implementation of the system will assist the production of finer surgical products.Read moreRead less
Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in bi ....Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in biomedical image analysis. This project will lead to fundamental contributions as well as techniques that address both problems: extraction of relevant features information from multisubject brain imaging data sets of the same modality or from fusion of brain imaging data sets collected from multimodalities.Read moreRead less