Name
Title | ||
|---|---|---|
Spatial Mixture Modelling For The Joint Detection-Estimation Of Brain Activity In Fmri |
Abstract | ||
|---|---|---|
Within-subject analysis in event-related functional Magnetic Resonance Imaging (fMRI) first relies on (i) a detection step to localize which parts of the brain are activated by a given stimulus type, and then on (ii) an estimation step to recover the temporal dynamics of the brain response. Recently, we have proposed a Bayesian detection-estimation approach that jointly addresses (i)-(ii) [1]. This approach provides both a spatial activity map and an estimate of brain dynamics. Here, we consider an extension that accounts for spatial correlation using a spatial mixture model (SMM) based on a binary Markov random field. It allows us to avoid any spatial smoothing of the data prior to the statistical analysis. Our simulation results support that SMM gives a better control of false positive (specificity) and false negative (sensitivity) rates than independent mixtures. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICASSP.2007.366682 | 2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PTS 1-3, PROCEEDINGS |
Keywords | Field | DocType |
Bayes procedures, biomedical signal detection, magnetic resonance imaging | Query optimization,Data mining,Data security,Relational database,Computer science,Range query (data structures),Sargable,View,Security analysis,Database,Cloud computing | Conference |
ISSN | Citations | PageRank |
1520-6149 | 10 | 1.11 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thomas Vincent | 1 | 320 | 27.52 |
| Philippe Ciuciu | 2 | 452 | 50.82 |
| Idier, J. | 3 | 566 | 59.01 |