Arterial Spin Labelling (ASL) functional Magnetic Resonance Imaging (fMRI) data provides a quantitative measure of blood perfusion, that can be correlated to neuronal activation. In contrast to BOLD measure, it is a direct measure of cerebral blood flow. However, ASL data has a lower SNR and resolution so that the recovery of the perfusion response of interest suffers from the contamination by a stronger hemodynamic component in the ASL signal. In this work we consider a model of both hemodynamic and perfusion components within the ASL signal. A physiological link between these two components is analyzed and used for a more accurate estimation of the perfusion response function in particular in the usual ASL low SNR conditions.
Cite
@article{arxiv.1501.01133,
title = {Physiologically Informed Bayesian Analysis of ASL fMRI Data},
author = {Aina Frau-Pascual and Thomas Vincent and Jennifer Sloboda and Philippe CIUCIU and Florence Forbes},
journal= {arXiv preprint arXiv:1501.01133},
year = {2015}
}