Faculty/School

Faculty of Science

School of Mathematical Sciences

Topic status

We're looking for students to study this topic.

Research centre

Centre for Biomedical Technologies

Supervisors

Dr Qianqian Yang
Position
Senior Lecturer
Division / Faculty
Faculty of Science

Overview

In 1985, the first image of water diffusion in the living human brain came to life. Since then significant developments have been made and diffusion magnetic resonance imaging (dMRI) has become a pillar of modern neuroimaging.

Over the last decade, combining computational modelling and diffusion MRI has enabled researchers to link millimetre scale diffusion MRI measures with microscale tissue properties, to infer microstructure information, such as diffusion anisotropy in white matter, axon diameters, axon density, intra/extra-cellular volume fractions, and fibre orientation distribution. This microstructure information can provide significant insights on the diagnosis, progress and treatment of diseases, such as stroke, tumour, Alzheimer’s disease, and multiple sclerosis.

However, conventional modelling frameworks were developed assuming Gaussian diffusion of water molecules in the living tissue, which violates what is observed in the diffusion MRI signals. Hence, new modelling frameworks and computational methods that can capture non-Gaussian diffusion are needed to advance the field of microstructure imaging in the brain.

Research engagement

diffusion MRI data analysis, parameter estimation, numerical simulations

Research activities

The student will work with Dr Qianqian Yang and her collaborators to

- explore brain diffusion MRI data,

- write MATLAB codes to estimate diffusion metrics from signal models, such as mono-exponential model, diffusional kurtosis imaging, and fractional diffusion models,

- write MATLAB codes to simulate water molecule diffusion in brain tissue.

Outcomes

We will aim to

- obtain brain parameter maps based on fractional diffusion parameters;

- understand the advantages and limitations of each signal model;

- establish links between fractional diffusion model parameters and tissue microstructure properties.

Skills and experience

We are looking for highly motivated students who are passionate about learning and research.

You should be familiar with differential equations and MATLAB. No prior knowledge on diffusion magnetic resonance imaging or brain tissue microstructure is required.

Start date

1 November, 2024

End date

15 February, 2025

Location

GP at QUT

Keywords

Contact

Dr Qianqian Yang, q.yang@qut.edu.au