Structural-functional connectivity in the brain. This project aims to develop magnetic resonance imaging analysis methods to non-invasively study brain connectivity. Recent advances in imaging can comprehensively describe the brain’s complex network of functional and structural connections (the brain ‘connectome’). This project will simultaneously investigate structural and functional connectivity, and characterise the dynamic properties of the connectome using graph-theoretic approaches. This p ....Structural-functional connectivity in the brain. This project aims to develop magnetic resonance imaging analysis methods to non-invasively study brain connectivity. Recent advances in imaging can comprehensively describe the brain’s complex network of functional and structural connections (the brain ‘connectome’). This project will simultaneously investigate structural and functional connectivity, and characterise the dynamic properties of the connectome using graph-theoretic approaches. This project should give neuroscientists computational tools to comprehensively map the network architecture of the human brain.Read moreRead less
In-vivo detection of airway injury and disease using phase contrast X-ray velocimetry. Currently diagnosis of lung disease, a major cause of death in humans, is based on clinical symptoms that do not usually manifest until the disease is well advanced. This project will develop a novel imaging technique, X-ray velocimetry, to detect changes in tissue before symptoms arise, potentially leading to strategies for managing lung diseases.
Discovery Early Career Researcher Award - Grant ID: DE150101655
Funder
Australian Research Council
Funding Amount
$297,036.00
Summary
Discriminative detection and quantification of cancer imaging biomarkers. This project aims to develop a new framework for the detection and quantification of cancer biomarkers in diagnostic and histopathology images with discriminative modelling of intrinsic structures. The framework will be the first computerised solution to provide automated, quantitative annotations of cancer imaging biomarkers at the macroscopic and microscopic levels to support standardised reporting of image interpretatio ....Discriminative detection and quantification of cancer imaging biomarkers. This project aims to develop a new framework for the detection and quantification of cancer biomarkers in diagnostic and histopathology images with discriminative modelling of intrinsic structures. The framework will be the first computerised solution to provide automated, quantitative annotations of cancer imaging biomarkers at the macroscopic and microscopic levels to support standardised reporting of image interpretation. It will help to alleviate the inter-observer variability and time-consuming process of manual analysis. The project aims to advance fundamental biomedical imaging research in generalised visual structure extraction and classification, and enable large-scale translational research in systems pathology for personalised cancer care.Read moreRead less
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.Read moreRead less
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.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101518
Funder
Australian Research Council
Funding Amount
$294,111.00
Summary
Multi-Object Recognition of Biomedical Images via Holistic Ontology. This project seeks to advance the development of new biomedical image recognition and analysis solutions by associating biomedical images with biomedical knowledge and personalised data. The provision of accurate and robust multi-object recognition and analysis from biomedical image data is a fundamental requirement for biomedical imaging applications. This project aims to improve the recognition and analysis of anatomical and ....Multi-Object Recognition of Biomedical Images via Holistic Ontology. This project seeks to advance the development of new biomedical image recognition and analysis solutions by associating biomedical images with biomedical knowledge and personalised data. The provision of accurate and robust multi-object recognition and analysis from biomedical image data is a fundamental requirement for biomedical imaging applications. This project aims to improve the recognition and analysis of anatomical and functional structures from biomedical images with ‘holistic ontology’ modelling that represents a multi-level biological, physiological, and anatomical knowledge base. The project will potentially have application in many health care areas, such as computer aided diagnosis, image-guided surgery planning, and image-based disease modelling.Read moreRead less
Novel technologies for motion-compensated simultaneous Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) imaging. The aim of this work is to develop motion tracking and motion correction techniques for an emerging hybrid imaging technology, MR-PET. The MR-PET scanner simultaneously acquires structural MR images and functional PET images. The work will provide clearer images without the effects of motion blur for both research and clinical applications.
Automated pathogen detection using time-gated luminescence microscopy. A rapid and general means of in-situ pathogen identification would benefit the community by ensuring that appropriate treatments can be applied in the early stages of a disease. Patient prognosis is thereby improved and opportunities for multi-drug resistant organisms to arise are limited. Time-gated luminescence microscopy (TgM) exploits persistent luminescence to overcome autofluorescence, a serious problem in pathogen dete ....Automated pathogen detection using time-gated luminescence microscopy. A rapid and general means of in-situ pathogen identification would benefit the community by ensuring that appropriate treatments can be applied in the early stages of a disease. Patient prognosis is thereby improved and opportunities for multi-drug resistant organisms to arise are limited. Time-gated luminescence microscopy (TgM) exploits persistent luminescence to overcome autofluorescence, a serious problem in pathogen detection. Drug-resistant 'Golden Staph' (MRSA) will be used as the model organism to evaluate TgM efficacy. Ultimately however, TgM will be applied for the detection of tuberculosis, a highly contagious disease affecting the respiratory system of more than one-third of the world's population.Read moreRead less
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