Category: Digital health imagine
Leading digital infrastructure
Underpinning our leading AI research, we will expand on the AIS platform, designing and implementing a suite of digital tools to accelerate AI imaging research, better utilise the university’s hardware […]
Explainable AI
In this project, we will study the research area “explainable AI” that enables the outputs from the AI systems to exhibit a certain degree of explainable capability in order for […]
Imaging enhancement using AI
This project aims to exploit advanced AI technologies to enhance the quality of MRI data to make it comparable to that obtained from time consuming high-quality research protocols. The increased […]
Imaging biomarkers from AI federated learning
This MRFF project seeks to build a novel, hybrid AI learning ecosystem to generate clinically-relevant biomarkers of disease progression for the common, disabling neurological condition, multiple sclerosis (MS). The MSBASE-XNAT […]
Human intelligence in AI loop
In this project, we will investigate how to introduce human intelligence in the loop when developing advanced AI methods, to progressively improve disease diagnosis results by taking advantage of both […]
Imaging analysis and AI
In this project, we will focus on cohesively developing advanced AI technologies to revolutionise imaging-based diagnosis of disease and extend our work towards commercial applications and clinical deployment. Specifically, we […]