Model Selection for Hemodynamic Brain Parcellation in fMRI

Mohanad Albughdadi 1 Lotfi Chaari 1 Florence Forbes 2 Jean-Yves Tourneret 1 Philippe Ciuciu 3
1 IRIT - Institut de recherche en informatique de Toulouse
2 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
3 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
Inria Saclay - Ile de France
Abstract : Brain parcellation into a number of hemodynamically homogeneous regions (parcels) is a challenging issue in fMRI analyses. This task has been recently integrated in the joint detection-estimation (JDE) resulting in the so-called joint detection-parcellation-estimation (JPDE) model. JPDE automatically estimates the parcels from the fMRI data but requires the desired number of parcels to be fixed. This is potentially critical in that the chosen number of parcels may influence detection-estimation performance. In this paper, we propose a model selection procedure to automatically fix the number of parcels from the data. The selection procedure relies on the calculation of the free energy corresponding to each concurrent model, within the variational expectation maximization framework. Experiments on synthetic and real fMRI data demonstrate the ability of the proposed procedure to select an adequate number of parcels.
Keywords : fMRI JPDE Parcellation JDE
Type de document :
Communication dans un congrès
EUSIPCO - 22nd European Signal Processing Conference, Sep 2014, Lisbon, Portugal. IEEE, pp.31 - 35, 2014, 〈http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6951965〉
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https://hal.inria.fr/hal-01107475
Contributeur : Florence Forbes <>
Soumis le : mardi 20 janvier 2015 - 17:51:19
Dernière modification le : mercredi 11 avril 2018 - 01:58:50

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Mohanad Albughdadi, Lotfi Chaari, Florence Forbes, Jean-Yves Tourneret, Philippe Ciuciu. Model Selection for Hemodynamic Brain Parcellation in fMRI. EUSIPCO - 22nd European Signal Processing Conference, Sep 2014, Lisbon, Portugal. IEEE, pp.31 - 35, 2014, 〈http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6951965〉. 〈hal-01107475〉

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