Thesis Project Form

Arterial Spin Labelling (ASL) is a non-invasive MRI technique that enables the quantification of Cerebral Blood Flow (CBF). ASL can be used to estimate cerebrovascular reactivity (CVR) i.e. the ability of cerebral blood vessels to respond to changes in arterial CO2, as a result of breath-hold. However, the ASL signal is subject to low signal-to-noise ratio, which can affect the estimation of CVR. This thesis will explore different denoising strategies and investigate their effects on the estimation of CVR mapping.

The candidate will develop a pipeline to preprocess and analyze ASL MRI data acquired during a breath-hold task. The candidate will investigate different denoising strategies and evaluate their effects on the CVR estimation. The candidate will perform the appropriate statistical analyses to evaluate the performance of denoising strategies to improve CVR estimation.

The thesis will provide practical training to the candidate, who will acquire the skills to implement and use advanced ASL MRI preprocessing and analysis pipelines, from raw ASL data to CVR estimation and statistical analysis, from both theoretical and practical perspectives. The candidate will gain experience in ASL preprocessing, CBF quantification, CVR estimation, and the application of different denoising strategies, using MATLAB-based tools.