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Involvement of the Human Retinal Endothelial Cell in Blinding Eye Disease. Endothelial cells line the blood vessels of the vascular networks that circulate blood through the tissues. The molecular constitution of each endothelial cell is different and specific to function, but may predispose to tissue-specific disease. Retinal endothelial cells ensure the nutrition and protection of a tissue critical to vision, but are key participants in retinal ischemic, inflammatory and infectious diseases th ....Involvement of the Human Retinal Endothelial Cell in Blinding Eye Disease. Endothelial cells line the blood vessels of the vascular networks that circulate blood through the tissues. The molecular constitution of each endothelial cell is different and specific to function, but may predispose to tissue-specific disease. Retinal endothelial cells ensure the nutrition and protection of a tissue critical to vision, but are key participants in retinal ischemic, inflammatory and infectious diseases that threaten vision. This project will investigate molecular activities of retinal endothelial cells that are relevant to retinal disease processes and explore future biological therapies directed against the human retinal endothelial cell that address efficacy and safety deficiencies of current treatments.Read moreRead less
Continuously learning to see. The ultimate goal of computer vision is to make a machine able to understand the world through analysis of images or videos. The new machine learning techniques developed in this project will enable previously impossible methods of computer vision and help strengthen Australia's competitiveness in this important area.
Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collabor ....Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collaborations with machine learning and medical image analysis research institutions. This should provide significant benefits, such as better understanding of deep learning theory, new deep learning applications that can use previously unexplored data sets, and training for the future Australian workforce.Read moreRead less