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
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. Read moreRead less
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.Read moreRead less
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.Read moreRead less
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
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.Read moreRead less
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".
Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100055
Funder
Australian Research Council
Funding Amount
$400,000.00
Summary
State-of-the-art upgrade to multi-transmit multi-receive technology for research dedicated 3 Tesla magnetic resonance imaging (MRI) scanner. Projects requiring the proposed infrastructure are aligned with two National Research Priorities. The research will lead to new methods for imaging and detecting soft tissue changes, identifying developmental, cognitive and degenerative disorders, and pharmacological research. The understanding of the basis of physiological, cognitive and biochemical proces ....State-of-the-art upgrade to multi-transmit multi-receive technology for research dedicated 3 Tesla magnetic resonance imaging (MRI) scanner. Projects requiring the proposed infrastructure are aligned with two National Research Priorities. The research will lead to new methods for imaging and detecting soft tissue changes, identifying developmental, cognitive and degenerative disorders, and pharmacological research. The understanding of the basis of physiological, cognitive and biochemical processes which will be facilitated by the new equipment will contribute to the priority area Promoting and Maintaining Good Health and will underpin an array of subsequent medical research. The new equipment will extend capabilities and training in signal analysis, biomedical engineering and biomedicine, contributing to the priority area Frontier technologies for Building and Transforming Australian Industries.Read moreRead less
Detection and Quantification of General Fetal Movements from Accelerometer Measurements using Nonstationary Signal Processing Techniques. There are approximately 1,750 fetal deaths per year in Australian with about one-third occurring late in gestation and without an apparent cause. The development of an automated system capable of long-term monitoring of fetal health will result in accurate diagnoses and prediction of future outcome. This will, in turn, allow early intervention by the clinicia ....Detection and Quantification of General Fetal Movements from Accelerometer Measurements using Nonstationary Signal Processing Techniques. There are approximately 1,750 fetal deaths per year in Australian with about one-third occurring late in gestation and without an apparent cause. The development of an automated system capable of long-term monitoring of fetal health will result in accurate diagnoses and prediction of future outcome. This will, in turn, allow early intervention by the clinician to reduce fetal deaths and enhance the chances of good outcomes with resultant savings in social and financial costs to the community. The development of such equipment would spawn future research into intervention treatments and contribute to Australia's position as a world leader in computerised health monitoring systems.Read moreRead less