Non-Parametric Modelling of Motion and Depth fields with Boundary Geometry for Scalable Compression and Dissemination. Applications for large format video surveillance are about to grow rapidly, starting with military applications and then moving into the civilian arena, highlighting the importance of compression for interactive dissemination, so as to make best use of limited communication channels. This project will develop an innovative representation for motion and depth/elevation maps, whi ....Non-Parametric Modelling of Motion and Depth fields with Boundary Geometry for Scalable Compression and Dissemination. Applications for large format video surveillance are about to grow rapidly, starting with military applications and then moving into the civilian arena, highlighting the importance of compression for interactive dissemination, so as to make best use of limited communication channels. This project will develop an innovative representation for motion and depth/elevation maps, which addresses a key obstacle in the deployment of technology for efficient interactive access to large format video and geospatial imagery. These applications are relevant to Australia's defence and infrastructure for smart information use. Moreover, this is a strategic proposal to strengthen Australia's existing lead in aspects of interactive media dissemination.Read moreRead less
Semantic Authentication of Visual Data. Data authentication systems can detect the smallest modification to a message. Authentication systems for media objects such as images, and audio and video clips have a different requirement they must ensure authenticity of the content without needing all the changes to be detectable. The aims of this project are to develop a framework for design and analysis of image and video authentication systems, and construct secure and flexible systems that can be ....Semantic Authentication of Visual Data. Data authentication systems can detect the smallest modification to a message. Authentication systems for media objects such as images, and audio and video clips have a different requirement they must ensure authenticity of the content without needing all the changes to be detectable. The aims of this project are to develop a framework for design and analysis of image and video authentication systems, and construct secure and flexible systems that can be used in practice. This research addresses the urgent need of providing security for multimedia objects in electronic commerce and is of high importance to the acceptance of advanced communication and information services.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
Highly Scalable Video Compression with Finely Embedded Motion Signalling. Highly scalable video compression is critical to the emergence of new applications in video distribution and management. Examples include interactive remote browsing of video and robust video surveillance over shared networks. Previous ARC funding produced fundamental breakthroughs in scalable video compression, resulting in a new paradigm which has been adopted by leading researchers in the field. The present project a ....Highly Scalable Video Compression with Finely Embedded Motion Signalling. Highly scalable video compression is critical to the emergence of new applications in video distribution and management. Examples include interactive remote browsing of video and robust video surveillance over shared networks. Previous ARC funding produced fundamental breakthroughs in scalable video compression, resulting in a new paradigm which has been adopted by leading researchers in the field. The present project addresses the two most important problems which currently limit the potential of this paradigm. Inspired by the applicant's recent discoveries, the outcomes of this project are likely to represent significant scientific breakthroughs and contribute to a new international video coding standard.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
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 data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medi ....A data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medicine, which recognises that there are important differences between individuals with a particular disease, and that when patients are separated into sub-populations with similar disease patterns, treatment can be tailored to these sub-populations.Read moreRead less
Omni-modality medical image analysis and visualisation. The term ‘Omni’-modality imaging (OMI) has been coined to describe the integration of multiple, complementary medical imaging modalities. However, there is currently a lack of an appropriate means to assimilate and derive maximum benefit from these integrated data. This project aims to provide a new approach to OMI data analysis and visualisation, by deriving a novel ‘level of relevance’ from the overlapping anatomical and pathological stru ....Omni-modality medical image analysis and visualisation. The term ‘Omni’-modality imaging (OMI) has been coined to describe the integration of multiple, complementary medical imaging modalities. However, there is currently a lack of an appropriate means to assimilate and derive maximum benefit from these integrated data. This project aims to provide a new approach to OMI data analysis and visualisation, by deriving a novel ‘level of relevance’ from the overlapping anatomical and pathological structures in the data which will be used to suppress superfluous data and highlight the most relevant data to maximise the information gained from the OMI data. Further, OMI visualisation is proposed to efficiently navigate through the overlapping data.Read moreRead less
A technology platform for multiple body site image-omics. The project aim is to derive a technology platform comprising new image processing and machine learning algorithms to integrate imaging and biological data across multiple body sites. The relationships between image features and biological data across multiple sites has not been discovered before. We propose the use of biological information from one sampled site to investigate other unsampled sites based on imaging-omics correspondences. ....A technology platform for multiple body site image-omics. The project aim is to derive a technology platform comprising new image processing and machine learning algorithms to integrate imaging and biological data across multiple body sites. The relationships between image features and biological data across multiple sites has not been discovered before. We propose the use of biological information from one sampled site to investigate other unsampled sites based on imaging-omics correspondences. We will use a data-driven, searchable graph model approach for knowledge discovery within the population data. The project will provide new insights into systems biology and bioinformatics that will then inform and promote benefits in life sciences, with potential future benefits in healthcare.Read moreRead less