System identification of microstructure in the brain using magnetic resonance imaging
There has been recent interest in methods that purport to identify microstructural features of the brain from diffusion-weighted magnetic resonance imaging (MRI) data. Inference on the axonal and cellular micron scale from images of two orders of magnitude less resolution requires accurate models of the tissue geometry and membrane permeabilities. We are applying system indentification and Bayesian analysis techniques to determine the veracity of such methods, and aim to characterise the limit of robust estimation that can be inferred from the raw MRI data.
Leader: Leigh Johnston
Students: Warda Syeda
Neuroengineering Research Laboratory
Convergence of engineering and IT with the life sciences
magnetic resonance imaging MRI; medical image analysis; neuroimaging; signals and systems