Industrial Transformation Training Centres - Grant ID: IC170100030
Funder
Australian Research Council
Funding Amount
$4,133,659.00
Summary
ARC Training Centre in Cognitive Computing for Medical Technologies. The ARC Training Centre in Cognitive Computing for Medical Technologies aims to create a workforce that is expert in developing, applying and interrogating cognitive computing technologies in data-intensive medical contexts. This will facilitate the next generation of data-driven and machine learning-based medical technologies. The Centre will provide a world-class industry-driven research training environment for PhD students ....ARC Training Centre in Cognitive Computing for Medical Technologies. The ARC Training Centre in Cognitive Computing for Medical Technologies aims to create a workforce that is expert in developing, applying and interrogating cognitive computing technologies in data-intensive medical contexts. This will facilitate the next generation of data-driven and machine learning-based medical technologies. The Centre will provide a world-class industry-driven research training environment for PhD students and postdoctoral researchers. These researchers will lead the medical technology industry into a new era of data-driven personalised and precision medical devices and applications. The Centre will result in the development of capabilities in the core technologies of machine learning and the practical application of cognitive computing in the area of health.Read moreRead less
Bridging the gap between global mechanics and regional imaging in the lungs. The detailed mechanics of breathing are not well understood, due to a lack of regional lung measurement techniques. This project aims to develop a powerful analysis tool to image in vivo mechanical properties of the lungs. The expected outcome of this project is a novel platform for investigation and understanding of lung function, enabling information previously only available for the whole lung to be calculated for lo ....Bridging the gap between global mechanics and regional imaging in the lungs. The detailed mechanics of breathing are not well understood, due to a lack of regional lung measurement techniques. This project aims to develop a powerful analysis tool to image in vivo mechanical properties of the lungs. The expected outcome of this project is a novel platform for investigation and understanding of lung function, enabling information previously only available for the whole lung to be calculated for local lung regions within the body. The image analysis methods developed are intended to enable respiratory researchers to investigate lung function in unprecedented detail, leading to new insights into the workings of this complicated and vital organ. Read moreRead less