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Australian State/Territory : QLD
Field of Research : Pattern Recognition
Research Topic : cancer/cachexia
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  • Funded Activity

    Discovery Projects - Grant ID: DP0772887

    Funder
    Australian Research Council
    Funding Amount
    $895,099.00
    Summary
    Multivariate Methods for the Analysis of Microarray Gene-Expression Data with Applications to Cancer Diagnostics. The project will benefit the Australian Society as a whole by developing statistical methodology for the analysis of high-throughput data. In particular, it will develop a novel and easily implemented model for the analysis of correlated and structured data that may be of high dimension. It thus has wide applicability to improving the quality and validity of applied research in most .... Multivariate Methods for the Analysis of Microarray Gene-Expression Data with Applications to Cancer Diagnostics. The project will benefit the Australian Society as a whole by developing statistical methodology for the analysis of high-throughput data. In particular, it will develop a novel and easily implemented model for the analysis of correlated and structured data that may be of high dimension. It thus has wide applicability to improving the quality and validity of applied research in most industries in Australia. More specifically, it is to be applied here to the diagnosis and prognosis of ovarian cancer. This cross-disciplinary project will strengthen Australian researchers' capacity and capability of participating in cutting-edge DNA microarray research.
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    Funded Activity

    Discovery Projects - Grant ID: DP0774601

    Funder
    Australian Research Council
    Funding Amount
    $170,000.00
    Summary
    RadioGenes2: Modelling complex biomolecular interactions in radiated tumours: Towards understanding the genesis of therapeutic radioresistance. About 45% of bladder cancer patients require radiotherapy or surgery. Radiotherapy has a failure rate of ~50%. Surgery (bladder removal) diminishes quality of life considerably. Modelling complex gene interactions in radiated cancer cells will provide crucial knowledge on the molecular genesis of radiotherapy-resistance of tumours. Our findings will prov .... RadioGenes2: Modelling complex biomolecular interactions in radiated tumours: Towards understanding the genesis of therapeutic radioresistance. About 45% of bladder cancer patients require radiotherapy or surgery. Radiotherapy has a failure rate of ~50%. Surgery (bladder removal) diminishes quality of life considerably. Modelling complex gene interactions in radiated cancer cells will provide crucial knowledge on the molecular genesis of radiotherapy-resistance of tumours. Our findings will provide: (i) an accurate mathematical/computational model for diagnosing radiosensitivity; (ii) further insights to be applied in the pharmaceutical sector such as the discovery of novel molecular targets that have the potential to increase radiotherapy success ratios; (iii) a holistic modelling technique applicable to a larger diversity of tumours.
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    Funded Activity

    Linkage Projects - Grant ID: LP0774994

    Funder
    Australian Research Council
    Funding Amount
    $501,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0879250

    Funder
    Australian Research Council
    Funding Amount
    $275,000.00
    Summary
    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.
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    Funded Activity

    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.
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