Biomedical Visual Image Analytics for Multi-disciplinary Retrieval. The project aims to develop a framework to provide users with the interactive access to information that is necessary for the best collaborative decision-making. Visual analytics theory is becoming increasing valuable for managing ‘big data’ because it can provide interactive and intuitive understanding of the rich information embedded within complex data and decision support systems. There are, however, fundamental challenges t ....Biomedical Visual Image Analytics for Multi-disciplinary Retrieval. The project aims to develop a framework to provide users with the interactive access to information that is necessary for the best collaborative decision-making. Visual analytics theory is becoming increasing valuable for managing ‘big data’ because it can provide interactive and intuitive understanding of the rich information embedded within complex data and decision support systems. There are, however, fundamental challenges that currently prevent visual analytics from being routinely applied to multi-disciplinary collaboration, which is now ‘the norm’ to solve large complicated problems where there is significant social impact. This project aims to address these challenges and improve visual analytics theory by developing a biomedical visual image analytics framework that enables interactive information retrieval of multidisciplinary databases.Read moreRead less
Multiscale integration of imaging and omics data. This project aims to integrate multiscale imaging and molecular data to characterise disease in patients. Modern healthcare needs to embrace ‘big (health) data’s potential to address an ageing population’s increasing healthcare demands and the inefficiencies and waste in patient treatment. This project expects to pioneer basic science research in methodologies to integrate, correlate and then derive knowledge from multi-scale data, to characteris ....Multiscale integration of imaging and omics data. This project aims to integrate multiscale imaging and molecular data to characterise disease in patients. Modern healthcare needs to embrace ‘big (health) data’s potential to address an ageing population’s increasing healthcare demands and the inefficiencies and waste in patient treatment. This project expects to pioneer basic science research in methodologies to integrate, correlate and then derive knowledge from multi-scale data, to characterise the mechanisms of disease in individual patients, in space and time. Its integrated model is expected to form the basis of a framework for individualised patient disease analysis.Read moreRead less
Application of manifold-based image analysis to identify subtle changes in digitally-captured pathology samples. This project will research and develop advanced computer aided analytics for digital pathology with the aim of automating several common pathology tests. This project should not only greatly increase the speed of pathology tests but should also improve quality, lower costs and improve patient outcomes.
Computational techniques for protease research. Protease research is an area of intensive research in Australia. Correctly assessing the mechanisms of protease function is crucial not only for improving our health through medical research and drug development, but also to multiple national areas of research and development, including biotechnology, agriculture, and industries such as the dairy industry. This project will develop innovative computational techniques to advance understanding of h ....Computational techniques for protease research. Protease research is an area of intensive research in Australia. Correctly assessing the mechanisms of protease function is crucial not only for improving our health through medical research and drug development, but also to multiple national areas of research and development, including biotechnology, agriculture, and industries such as the dairy industry. This project will develop innovative computational techniques to advance understanding of how proteases function by redressing a common research assumption that can significantly affect the accuracy of protease function prediction. The outcomes will improve fundamental research into proteases, and enable improved research and development in the many fields that rely on protease work.Read moreRead less
Robotic gait assistive strategy for people with paraplegia: Generating balanced and human-like gait on a bipedal system. The outcomes of the project will contribute significantly to the fundamental understanding of bipedal mechanisms, robotics, and the dynamics of human gait. This research is unique in Australia and it will strengthen Australia's research standing in robotics and health-sciences. The immediate application of the outcomes will contribute significantly to the musculoskeletal and p ....Robotic gait assistive strategy for people with paraplegia: Generating balanced and human-like gait on a bipedal system. The outcomes of the project will contribute significantly to the fundamental understanding of bipedal mechanisms, robotics, and the dynamics of human gait. This research is unique in Australia and it will strengthen Australia's research standing in robotics and health-sciences. The immediate application of the outcomes will contribute significantly to the musculoskeletal and psychological health of people with spinal cord injury, as well as the basic locomotion capability around the house to carry out their daily tasks more independently and conveniently. Hence it will directly contribute to improving their quality of life and substantially reducing health-care costs and carer responsibilities in the community.Read moreRead less
Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored ....Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored to individual characteristics. The success of this project could significantly advance the fundamental research in image analysis. Expected outcomes include new knowledge and algorithms for image analysis, which could benefit fields like biology and archaeology, where labeled images are hard to attain and scarce.Read moreRead less
On-line and Incremental EM-based Neural Networks: Application to Hospital Utlilization and Gene Expression Data. Artificial neural networks have been widely applied as universal classifiers in many fields, such as biomedicine. However, misunderstanding of fundamental statistical principles, which can cause misleading findings, has been frequently observed in the literature. This project aims to integrate statistical methodologies in neural networks to provide a unified approach to improve its ....On-line and Incremental EM-based Neural Networks: Application to Hospital Utlilization and Gene Expression Data. Artificial neural networks have been widely applied as universal classifiers in many fields, such as biomedicine. However, misunderstanding of fundamental statistical principles, which can cause misleading findings, has been frequently observed in the literature. This project aims to integrate statistical methodologies in neural networks to provide a unified approach to improve its applicability and efficiency in implementation. The system developed from this proposed cross-disciplinary research will be applied to hospital utilization data (hospital morbidity database, Western Australia) and gene expression data (DNA microarrays databases, Harvard University). This collaborative research will advance the international standard of Australian research communities.
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An integrated virtual functional human body (VFHB). This research is aimed at extracting and harnessing new knowledge from the immense volume of biomedical imaging data that is currently generated in healthcare through innovative information technologies. These technologies will allow a ‘virtual functional human body’ in a realistic, comprehensible visual format to be built, which will be accessible to researchers and lay individuals. It is expected that it will lead to a paradigm-change in the ....An integrated virtual functional human body (VFHB). This research is aimed at extracting and harnessing new knowledge from the immense volume of biomedical imaging data that is currently generated in healthcare through innovative information technologies. These technologies will allow a ‘virtual functional human body’ in a realistic, comprehensible visual format to be built, which will be accessible to researchers and lay individuals. It is expected that it will lead to a paradigm-change in the delivery of information systems, scientific discovery and impact on a lay individual's perception of their health status such that it will empower them to actively participate in their health and general well-being.Read moreRead less