Abstract
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.
Keywords
- Blood Oxygen Level Dependent
- Arterial Spin Labelling
- Physiological Model
- Blood Oxygen Level Dependent Signal
- Blood Oxygen Level Dependent Response
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Frau-Pascual, A., Vincent, T., Sloboda, J., Ciuciu, P., Forbes, F. (2014). Physiologically Informed Bayesian Analysis of ASL fMRI Data. In: Cardoso, M.J., Simpson, I., Arbel, T., Precup, D., Ribbens, A. (eds) Bayesian and grAphical Models for Biomedical Imaging. Lecture Notes in Computer Science, vol 8677. Springer, Cham. https://doi.org/10.1007/978-3-319-12289-2_4
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DOI: https://doi.org/10.1007/978-3-319-12289-2_4
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12288-5
Online ISBN: 978-3-319-12289-2
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