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Research Topic : intelligence
Socio-Economic Objective : Diagnostic methods
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  • Researchers (29)
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  • Funded Activity

    Linkage Projects - Grant ID: LP0212081

    Funder
    Australian Research Council
    Funding Amount
    $331,196.00
    Summary
    Learning Medical Image Knowledge. We aim to develop Machine Learning and Knowledge Acquisition techniques for automated recognition of features in medical images, and to provide decision support for diagnosis from medical images. The project is innovative in its use of layered learning, where the computer first learns to recognise low-level image features that are then used to learn more complex features. The project is also innovative in combining a variety of automatic learning methods, includ .... Learning Medical Image Knowledge. We aim to develop Machine Learning and Knowledge Acquisition techniques for automated recognition of features in medical images, and to provide decision support for diagnosis from medical images. The project is innovative in its use of layered learning, where the computer first learns to recognise low-level image features that are then used to learn more complex features. The project is also innovative in combining a variety of automatic learning methods, including relational learning, with human-assisted knowledge acquisition methods. The expected outcomes will be new techniques for image understanding, particularly for our test domain, namely, High Resolution Computed Tomography scans of the lung.
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    Funded Activity

    Linkage Projects - Grant ID: LP0669420

    Funder
    Australian Research Council
    Funding Amount
    $147,900.00
    Summary
    Quantitative measurement of Schizophrenia using Electrovestibulography. Schizophrenia was estimated to cost approximately $1.85billion in 2001 (0.3% of GDP and nearly $50k for each of the 37,000 Australians with the illness). Over one third of the cost is borne by sufferers and their carers. Misdiagnosis and incorrect therapy are common. To date quantitative assessment of Schizophrenics has been impossible making this tool potentially invaluable. An accurate diagnostic test could facilitate earl .... Quantitative measurement of Schizophrenia using Electrovestibulography. Schizophrenia was estimated to cost approximately $1.85billion in 2001 (0.3% of GDP and nearly $50k for each of the 37,000 Australians with the illness). Over one third of the cost is borne by sufferers and their carers. Misdiagnosis and incorrect therapy are common. To date quantitative assessment of Schizophrenics has been impossible making this tool potentially invaluable. An accurate diagnostic test could facilitate earlier diagnosis, more accurate treatment plans, and prevention of debilitating psychotic episodes for the sufferer. By being able to monitor drug efficacy the community can benefit by reduced drug costs, confinement times and hastened new drug development.
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    Funded Activity

    Linkage Projects - Grant ID: LP0991295

    Funder
    Australian Research Council
    Funding Amount
    $280,000.00
    Summary
    Feature Detection and Computer-aided Diagnosis with Longitudinal Tracking of Benign Asbestos-Related Pleural Disease in CT images. This project seeks to develop smart and novel feature extraction and knowledge acquisition techniques to assist radiologists in automated diagnosis and assessment of lung diseases. These outcomes will lead to improved delivery of health services in Australia, including in rural regions. They will lead to more accurate assessment of asbestos related pleural diseases f .... Feature Detection and Computer-aided Diagnosis with Longitudinal Tracking of Benign Asbestos-Related Pleural Disease in CT images. This project seeks to develop smart and novel feature extraction and knowledge acquisition techniques to assist radiologists in automated diagnosis and assessment of lung diseases. These outcomes will lead to improved delivery of health services in Australia, including in rural regions. They will lead to more accurate assessment of asbestos related pleural diseases for compensation and treatment and better followup, leading to earlier treatment and better quality of life for patients suffering from lung diseases. The project will also save costs due to automated assessment as well as the potential for fewer patient scans.
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    Funded Activity

    Discovery Projects - Grant ID: DP1097059

    Funder
    Australian Research Council
    Funding Amount
    $150,000.00
    Summary
    Automatic Brain Tissue Segmentation in Magnetic Resonance Images based on Knowledge-guided Constrained Clustering. Accurate volumetric measurement of brain tissues is of critical importance in the study of many brain disorders, disease diagnosis, disease progression tracking and treatment monitoring. The study in this research will result in the development of a powerful computational technique that allows automatic volumetric measurement and analysis of brain tissues. The software developed in .... Automatic Brain Tissue Segmentation in Magnetic Resonance Images based on Knowledge-guided Constrained Clustering. Accurate volumetric measurement of brain tissues is of critical importance in the study of many brain disorders, disease diagnosis, disease progression tracking and treatment monitoring. The study in this research will result in the development of a powerful computational technique that allows automatic volumetric measurement and analysis of brain tissues. The software developed in this project will expedite early clinical diagnosis and treatment of neural diseases for patients, hence saving life and reducing health cost both at the personal and the national level.
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    Funded Activity

    Discovery Projects - Grant ID: DP0773584

    Funder
    Australian Research Council
    Funding Amount
    $210,000.00
    Summary
    Automatic detection of the circle of Willis in neuro-images using multi-scale gradient calculation and knowledge-based genetic algorithms. Stroke is the third most common cause of death and a major contributor to long term disability in Australia. The most efficient way of preventing stroke from happening is to detect related symptoms early. The group of cerebral blood vessels that closely related to strokes is the circle of Willis (CoW). We build a system that can automatically detect and quan .... Automatic detection of the circle of Willis in neuro-images using multi-scale gradient calculation and knowledge-based genetic algorithms. Stroke is the third most common cause of death and a major contributor to long term disability in Australia. The most efficient way of preventing stroke from happening is to detect related symptoms early. The group of cerebral blood vessels that closely related to strokes is the circle of Willis (CoW). We build a system that can automatically detect and quantify CoW in neuroimages, providing ways of preventing strokes from happening. The project will enhance Australia¡¯s leading position in promoting and maintaining good health, especially in preventive healthcare.
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    Funded Activity

    Discovery Projects - Grant ID: DP1094173

    Funder
    Australian Research Council
    Funding Amount
    $180,000.00
    Summary
    Novel Motion Correction Technologies for Simultaneous Positron Emission Tomography and Magnetic Resonance Imaging. The recent development of the world's first prototype combined MR-PET scanner for human use has prompted immense interest. MR-PET is likely to revolutionize clinical diagnosis and basic research, by providing exquisite structural images co-registered with simultaneous functional PET images. We will exploit the as yet unexplored potential for motion information derived from the MR sy .... Novel Motion Correction Technologies for Simultaneous Positron Emission Tomography and Magnetic Resonance Imaging. The recent development of the world's first prototype combined MR-PET scanner for human use has prompted immense interest. MR-PET is likely to revolutionize clinical diagnosis and basic research, by providing exquisite structural images co-registered with simultaneous functional PET images. We will exploit the as yet unexplored potential for motion information derived from the MR system to be used to correct the simultaneously acquired PET data for patient motion. This research is an excellent opportunity for Australian researchers to make important contributions to an emerging technology with high economic potential, and will strengthen Australia's international position in engineering and biomedical systems development.
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    Funded Activity

    Discovery Projects - Grant ID: DP0878483

    Funder
    Australian Research Council
    Funding Amount
    $250,070.00
    Summary
    Determination of lung morphology from X-ray phase contrast radiographs. Current methods of imaging the lung rely heavily on low contrast images obtained with chest radiography or computed tomography. This research will develop new X-ray phase contrast imaging techniques capable of providing a tenfold contrast increase over conventional chest radiography at a fraction of the X-ray dose of computed tomography. Methods of extracting quantitative information on lung morphology and pathology from pha .... Determination of lung morphology from X-ray phase contrast radiographs. Current methods of imaging the lung rely heavily on low contrast images obtained with chest radiography or computed tomography. This research will develop new X-ray phase contrast imaging techniques capable of providing a tenfold contrast increase over conventional chest radiography at a fraction of the X-ray dose of computed tomography. Methods of extracting quantitative information on lung morphology and pathology from phase contrast chest radiographs will be developed during this research. Eventual outcomes are likely to lead to improved methods of detecting lung disease and injury for both biomedical and clinical studies.
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    Funded Activity

    Discovery Projects - Grant ID: DP0881063

    Funder
    Australian Research Council
    Funding Amount
    $289,972.00
    Summary
    Innovative visualization of next-generation biomedical images. This project addresses the difficult problems associated with managing the vast amounts of data that are currently available with advanced imaging devices and displaying these data so that the maximum amount of information can be extracted. Developing visualization capabilities for such data is not a trivial undertaking but the outcome of this research will produce enabling visualization technologies that will significantly impact th .... Innovative visualization of next-generation biomedical images. This project addresses the difficult problems associated with managing the vast amounts of data that are currently available with advanced imaging devices and displaying these data so that the maximum amount of information can be extracted. Developing visualization capabilities for such data is not a trivial undertaking but the outcome of this research will produce enabling visualization technologies that will significantly impact the life science, biomedical research and the way clinicians view and use these data for patient management. These technologies will have broad applications across biology and molecular science and will enhance Australia's leading position in the development of frontier technologies.
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    Funded Activity

    Discovery Projects - Grant ID: DP0877414

    Funder
    Australian Research Council
    Funding Amount
    $250,000.00
    Summary
    Intelligent Image Processing Techniques for Novel Biomarker Discovery. This project will make an impact on Australia's international research profile by seeking a solution to a worldwide challenging problem in biomarker discovery for the detection of diseases at an early stage which requires the incorporation of the skills and knowledge from biology, medicine, engineering, computer science, and information technology. The successful outcomes of this research will make an impact on Australia's e .... Intelligent Image Processing Techniques for Novel Biomarker Discovery. This project will make an impact on Australia's international research profile by seeking a solution to a worldwide challenging problem in biomarker discovery for the detection of diseases at an early stage which requires the incorporation of the skills and knowledge from biology, medicine, engineering, computer science, and information technology. The successful outcomes of this research will make an impact on Australia's engagement in using advanced image analysis and intelligent methods for the emerging research and development of targeted drug discovery.
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    Funded Activity

    Discovery Projects - Grant ID: DP0559755

    Funder
    Australian Research Council
    Funding Amount
    $218,000.00
    Summary
    Evolutionary algorithms for problems in functional genomics data analysis. Skin cancer has a high incidence in the Australian population. Schizophrenia is a psychiatric disorder that affects a significant proportion of the population worldwide. Both illnesses have genetic roots and can be triggered by environmental factors. We will uncover genetic relationship to disease and their responses to environmental conditions using computational methods and mathematical algorithms that can aid in the de .... Evolutionary algorithms for problems in functional genomics data analysis. Skin cancer has a high incidence in the Australian population. Schizophrenia is a psychiatric disorder that affects a significant proportion of the population worldwide. Both illnesses have genetic roots and can be triggered by environmental factors. We will uncover genetic relationship to disease and their responses to environmental conditions using computational methods and mathematical algorithms that can aid in the determination of function, especially in disease states. Understanding the complex genetic interactions that trigger these illnesses would give great benefits in preventive health care, skin cancer and schizophrenia genetic basis, and may lay the ground for building new methods for "personalized medicine".
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