Multi-subject joint parcellation detection estimation in functional MRI
- Resource Type
- Conference
- Authors
- Albughdadi, Mohanad; Chaari, Lotfi; Forbes, Florence; Tourneret, Jean-Yves; Ciuciu, Philippe
- Source
- 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on. :74-77 Apr, 2016
- Subject
- Bioengineering
Signal Processing and Analysis
Estimation
Brain modeling
Analytical models
Computational modeling
Data models
Covariance matrices
Hemodynamics
multi-subject fMRI analysis
JPDE
Par-cellation
Hemodynamic Response Function
VEM
- Language
- ISSN
- 1945-8452
fMRI experiments are usually conducted over a population of interest for investigating brain activity across different regions stimuli and objects. Multi-subject analysis proceeds in two steps, intra-subject analysis is performed sequentially on each individual and then group-level analysis is addressed to report significant results at the population level. This paper considers an existing Joint Parcellation Detection Estimation (JPDE) model which performs joint hemodynamic parcellation, brain dynamics estimation and evoked activity detection. The hierarchy of the JPDE model is extended for multi-subject analysis in order to perform group-level parcellation. Then, the corresponding underlying dynamics is estimated in each parcel while the detection and estimation steps are iterated over each individual. Validation on synthetic and real fMRI data shows its robustness in inferring the group-level parcellation and the corresponding hemodynamic profiles.