Automatic cartilage segmentation in magnetic resonance imaging. Osteoarthritis (OA) is the most common form of arthritis, affecting nearly 1.4 million Australians. This research aims at engineering new tools for use in Magnetic Resonance Imaging systems to enable automated analyses of the cartilage and bones in joint images. The goals of the work are to assist with improved diagnosis and treatment planning for both chronic disease, such as OA, and acute injuries, such as cartilage and ligament ....Automatic cartilage segmentation in magnetic resonance imaging. Osteoarthritis (OA) is the most common form of arthritis, affecting nearly 1.4 million Australians. This research aims at engineering new tools for use in Magnetic Resonance Imaging systems to enable automated analyses of the cartilage and bones in joint images. The goals of the work are to assist with improved diagnosis and treatment planning for both chronic disease, such as OA, and acute injuries, such as cartilage and ligament tears in sporting injuries and other traumas.
The software developed will be provided on the project’s partner (Siemens) platform and will therefore be available worldwide and have a consequently large impact on the field.
Read moreRead less
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
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. Read moreRead less
Investigation of three dimensional terahertz computed tomography for biomedical applications. Terahertz (T-ray) imaging is an exciting newly emerging technology that can perform safe, non-invasive, imaging and chemical sensing at the same time. This research aims to achieve an advance in terahertz imaging by using advanced methods that will enhance our ability to achieve accurate detection of diseased tissue in vivo. Socio-economic benefits to Australia include: (i) contributions to terahertz sy ....Investigation of three dimensional terahertz computed tomography for biomedical applications. Terahertz (T-ray) imaging is an exciting newly emerging technology that can perform safe, non-invasive, imaging and chemical sensing at the same time. This research aims to achieve an advance in terahertz imaging by using advanced methods that will enhance our ability to achieve accurate detection of diseased tissue in vivo. Socio-economic benefits to Australia include: (i) contributions to terahertz systems, enhancing Australia's reputation for cutting-edge research; (ii) international collaboration will be strengthened; (iii) results will potentially lead to commercialisation opportunities; (iv) the outcomes will ultimately impact on improving terahertz imaging in quality control, medical diagnosis, and detection for national security.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.