Advanced image processing methods for diffusion MRI

Furthering the capabilities of in vivo tissue microstructure analysis in neuroscience

Diffusion Magnetic Resonance Imaging (MRI) provides unique insight into the microstructure of neuronal tissue, by exploiting the random motion of water molecules as they interact with that tissue. Using appropriate mathematical models and advanced image processing techniques enables the quantitative assessment of white matter properties and their associations with various neuroscientific effects of interest. It is also possible to utilise the estimations of fibre bundle orientations within the brain white matter to digitally reconstruct the structural connectivity between grey matter areas using tractography methods.

Researchers at The Florey have historically been at the forefront of diffusion MRI methods development. Particular points of focus have been the Fixel-Based Analysis (FBA) framework[1], which provides statistical analysis of quantitative white matter measures in a manner that is tailored to the complex fibrous nature of the brain white matter, and methods for robust and quantitative evaluation of connectivity between grey matter regions[2].

A student with a talent for problem solving within complex systems will have the opportunity to participate in the evolution of these methods, improving the capabilities of neuroimaging analyses worldwide and ensuring that advances in image acquisition and quality are fully utilised within state-of-the-art analysis pipelines.

[1] Raffelt et al. Investigating white matter fibre density and morphology using fixel-based analysis. NeuroImage 2017:144;58-73
[2] Smith et al. Quantitative streamlines tractography: methods and inter-subject normalisation. 10.31219/osf.io/c67kn