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
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
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
An integrated virtual functional human body (VFHB). This research is aimed at extracting and harnessing new knowledge from the immense volume of biomedical imaging data that is currently generated in healthcare through innovative information technologies. These technologies will allow a ‘virtual functional human body’ in a realistic, comprehensible visual format to be built, which will be accessible to researchers and lay individuals. It is expected that it will lead to a paradigm-change in the ....An integrated virtual functional human body (VFHB). This research is aimed at extracting and harnessing new knowledge from the immense volume of biomedical imaging data that is currently generated in healthcare through innovative information technologies. These technologies will allow a ‘virtual functional human body’ in a realistic, comprehensible visual format to be built, which will be accessible to researchers and lay individuals. It is expected that it will lead to a paradigm-change in the delivery of information systems, scientific discovery and impact on a lay individual's perception of their health status such that it will empower them to actively participate in their health and general well-being.Read moreRead less
New techniques to detect fetal heart abnormalities. Australia’s national fetal death rate is 6.7 per one thousand births. In Australia’s Indigenous community it surges to 12.3 deaths per one thousand births. Early diagnosis (and management) of abnormal fetu.ses with cardiac defects will go a long way in reducing these numbers. The proposed technology will help set up easy-to-use systems for fetal cardiac abnormality screening and reduce fetal deaths and congenital heart disease burden in adult l ....New techniques to detect fetal heart abnormalities. Australia’s national fetal death rate is 6.7 per one thousand births. In Australia’s Indigenous community it surges to 12.3 deaths per one thousand births. Early diagnosis (and management) of abnormal fetu.ses with cardiac defects will go a long way in reducing these numbers. The proposed technology will help set up easy-to-use systems for fetal cardiac abnormality screening and reduce fetal deaths and congenital heart disease burden in adult life. This project will also provide domain trained researchers with cutting edge international academic and industry expertise.Read moreRead less