Physiologically Informed Bayesian Analysis of ASL fMRI Data

摘要

Arterial Spin Labelling (ASL) functional Magnetic Resonance Imaging (fMRI)data provides a quantitative measure of blood perfusion, that can be correlatedto neuronal activation. In contrast to BOLD measure, it is a direct measure ofcerebral blood flow. However, ASL data has a lower SNR and resolution so thatthe recovery of the perfusion response of interest suffers from thecontamination by a stronger hemodynamic component in the ASL signal. In thiswork we consider a model of both hemodynamic and perfusion components withinthe ASL signal. A physiological link between these two components is analyzedand used for a more accurate estimation of the perfusion response function inparticular in the usual ASL low SNR conditions.