Fast joint detection-estimation of evoked brain activity in event-related fMRI using a variational approach - Archive ouverte HAL Access content directly
Journal Articles IEEE Transactions on Medical Imaging Year : 2013

Fast joint detection-estimation of evoked brain activity in event-related fMRI using a variational approach

(1, 2) , (1, 2) , (2) , (3) , (1)
1
2
3

Abstract

In standard within-subject analyses of event-related fMRI data, two steps are usually performed separately: detection of brain activity and estimation of the hemodynamic response. Because these two steps are inherently linked, we adopt the socalled region-based Joint Detection-Estimation (JDE) framework that addresses this joint issue using a multivariate inference for detection and estimation. JDE is built by making use of a regional bilinear generative model of the BOLD response and constraining the parameter estimation by physiological priors using temporal and spatial information in a Markovian model. In contrast to previous works that use Markov Chain Monte Carlo (MCMC) techniques to sample the resulting intractable posterior distribution, we recast the JDE into a missing data framework and derive a Variational Expectation-Maximization (VEM) algorithm for its inference. A variational approximation is used to approximate the Markovian model in the unsupervised spatially adaptive JDE inference, which allows automatic fine-tuning of spatial regularization parameters. It provides a new algorithm that exhibits interesting properties in terms of estimation error and computational cost compared to the previously used MCMC-based approach. Experiments on artificial and real data show that VEM-JDE is robust to model misspecification and provides computational gain while maintaining good performance in terms of activation detection and hemodynamic shape recovery.
Fichier principal
Vignette du fichier
Chaari_2012_Fast_joint_MA.pdf (2.38 Mo) Télécharger le fichier
Vignette du fichier
inserm-00753873_edited.pdf (1.49 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Loading...

Dates and versions

inserm-00753873 , version 1 (19-11-2012)

Identifiers

Cite

Lotfi Chaari, Thomas Vincent, Florence Forbes, Michel Dojat, Philippe Ciuciu. Fast joint detection-estimation of evoked brain activity in event-related fMRI using a variational approach. IEEE Transactions on Medical Imaging, 2013, 32 (5), pp.821-837. ⟨10.1109/TMI.2012.2225636⟩. ⟨inserm-00753873⟩
480 View
385 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More