Predicting misdiagnoses in the transition from competence to expertise. This project aims to test whether the utilisation of cues predicts vulnerability to misdiagnosis during skill acquisition. This project uses newly developed measures of cue utilisation, together with innovative, on-line scenarios and a longitudinal design, to measure different types of misdiagnosis amongst qualified radiologists, pathologists and pilots as they acquire expertise. With potential applications in medicine, avia ....Predicting misdiagnoses in the transition from competence to expertise. This project aims to test whether the utilisation of cues predicts vulnerability to misdiagnosis during skill acquisition. This project uses newly developed measures of cue utilisation, together with innovative, on-line scenarios and a longitudinal design, to measure different types of misdiagnosis amongst qualified radiologists, pathologists and pilots as they acquire expertise. With potential applications in medicine, aviation, energy, transportation, and defence, the expected outcomes will facilitate interventions such as targeted training and the provision of technical support, that will guide the diagnostic process and thereby reduce the impact of misdiagnoses on individuals and infrastructure.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
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
A new look at perceptual expertise: the attentional Gestalt framework. This project aims to propose and rigorously test a new, mechanistic framework for understanding how training and experience alters our capacity to perceive and engage in skilled visual processing. The project intends to explain why trained visual experts often rapidly perceive things that elude novices. Expected outcomes of the project include new knowledge about the key mechanistic features that underlie skilled visual perfo ....A new look at perceptual expertise: the attentional Gestalt framework. This project aims to propose and rigorously test a new, mechanistic framework for understanding how training and experience alters our capacity to perceive and engage in skilled visual processing. The project intends to explain why trained visual experts often rapidly perceive things that elude novices. Expected outcomes of the project include new knowledge about the key mechanistic features that underlie skilled visual performance. Intended benefits of this knowledge include the development of artificial systems and improved training environments to facilitate and enhance human expert visual processing.Read moreRead less
Predicting the diagnostic performance of individuals and organisations. Predicting the diagnostic performance of individuals and organisations. This project aims to address diagnostic error in advanced technology systems, by providing a mechanism to assess and improve individual diagnosticians’ performance. Organisations that rely on their employees’ diagnostic skills rarely assess them once the operators become qualified, so there is no basis for interventions that might prevent diagnostic erro ....Predicting the diagnostic performance of individuals and organisations. Predicting the diagnostic performance of individuals and organisations. This project aims to address diagnostic error in advanced technology systems, by providing a mechanism to assess and improve individual diagnosticians’ performance. Organisations that rely on their employees’ diagnostic skills rarely assess them once the operators become qualified, so there is no basis for interventions that might prevent diagnostic errors affecting thousands. This research tests a new method of assessing diagnostic skills based on how skilled operators respond to cues. This project will test how employees’ diagnostic skills change and whether this change corresponds to measures of organisational performance. This research is expected to provide organisations with a tool to pre-empt diagnostic errors that could minimise costs to the economy.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
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.