Magnetic resonance imaging (MRI) is a tool used to produce 3-dimensional images of the internal structure of the body. These images are used regularly in the diagnosis and monitoring of brain related illnesses such as Alzheimer’s, multiple sclerosis (MS) and Glioblastoma (or brain cancer). MRIs provide a spatial representation of tissue microstructure from which it is possible to identify abnormalities that may represent the onset or progression of a disease. Generating these images from raw MRI signals requires processing a large volume of data and relies heavily on mathematical and computational techniques.
As the accuracy of MRI technology continues to improve, there is recognised value in using MRIs to determine patient disease prognosis. However, this is a non-trivial task since complex, potentially noisy, MRI data must be linked to models of disease progression. To achieve this, new methods in mathematical modelling and computational data science are needed to both improve the accuracy of MRIs and our ability to diagnose and predict patient outcomes.
This research group aims to develop new methods that will improve imaging technology and analysis and result in better patient care. Recently awarded Faculty of Science Research Group funding, this group plans to establish new avenues of research and collaborations domestically and abroad over the coming three years.
If you’re interested please get in contact with one of our group members.
Chief Investigators
- Professor Richi Nayak
- Dr Adrianne Jenner
- Dr David Warne
- Dr Qianqian Yang
- Dr Thirunavukarasu Balasubramaniam