Physiologically Informed Bayesian Analysis of ASL fMRI Data

Aina Frau-Pascual 1, 2 Thomas Vincent 1 Jennifer Sloboda 1 Philippe Ciuciu 3, 2 Florence Forbes 1
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
2 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
NEUROSPIN - Service NEUROSPIN, Inria Saclay - Ile de France
3 CEA - Commissariat à l'énergie atomique et aux énergies alternatives
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.
Document type :
Conference papers
Complete list of metadatas

Cited literature [12 references]  Display  Hide  Download
https://hal.inria.fr/hal-01100266
Contributor : Aina Frau-Pascual <>
Submitted on : Tuesday, January 6, 2015 - 11:07:08 AM
Last modification on : Thursday, March 14, 2019 - 7:54:04 AM
Long-term archiving on : Wednesday, June 3, 2015 - 5:11:29 PM

Files

14bambi_af_tv_js_pc_ff.pdf
Files produced by the author(s)

Identifiers

Collections

CEA | INRIA | INSMI | LJK | LJK_PS | LJK_PS_MISTIS | UGA | CEA-DRF | JOLIOT | NEUROSPIN

Citation

Aina Frau-Pascual, Thomas Vincent, Jennifer Sloboda, Philippe Ciuciu, Florence Forbes. Physiologically Informed Bayesian Analysis of ASL fMRI Data. BAMBI 2014 - First International Workshop on Bayesian and grAphical Models for Biomedical Imaging, Sep 2014, Boston, United States. pp.37 - 48, ⟨10.1007/978-3-319-12289-2_4⟩. ⟨hal-01100266⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

1094

Files downloads

376

Contact


archive-ouverte@inria.fr