Inferring brain tissue microstructure from standard structural imaging

Lead Research Organisation: Cardiff University
Department Name: School of Physics and Astronomy


The characterisation of brain structure in vivo and non-invasively is crucial for understanding biological processes in health and disease. One technique used to perform such a characterisation is diffusion Magnetic Resonance Imaging (dMRI), which allows to depict brain tissue structure with exquisite detail. Despite of all the advantages provided by dMRI, it has a major limitation: the acquisition time. For this reason, dMRI measurements are not usually part of routine imaging protocols, which usually focus on more standardised structural measurements. This limits the usability of clinical data for preforming accurate computational experiments to better inform the medical diagnosis. Then, there exist an interest in inferring brain tissue microstructure based on available information, such as standard structural images. If achieved, this would also be of unprecedented importance for speeding-up dMRI acquisitions by using the generated data as prior knowledge in the corresponding post-processing analysis. In this project, the student will address the issue by using artificial intelligence tools to predict personalised information of brain tissue micro-architecture using statistical models based on existing, high-quality data. This idea is grounded on the hypothesis that there exists a relationship between tissue anisotropy from one part, and scalar magnetic properties (e.g. T1, T2) and morphology from another part, which will be modelled statistically based on training data available in CUBRIC. This will be done by designing and implementing a data-driven statistical learning framework based on partial least squares regression models. The implementation in the graphical processing unit (GPU) will be pursued for speeding-up the computing time.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023992/1 01/04/2019 30/09/2027
2429404 Studentship EP/S023992/1 01/10/2020 30/09/2024 Matthew Ramsay Walker