Name
Abstract | ||
|---|---|---|
A fundamental question in functional MRI (fMRI) data analysis is to declare pixels either activated or non-activated with respect to the experimental design. A new statistical test for detecting activated pixels in fMRI data is proposed. The test is based on comparing the dimension of the parametric models fitted to the voxels fMRI time series data with and without controlled activation-baseline pattern. A corrected variant of the Akaike information criterion, is used for this comparison. This test has the advantage of not requiring any user-specified threshold to be estimated. The effectiveness of the proposed fMRI activation detection method is illustrated on real experimental data. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/SSP.2012.6319669 | Statistical Signal Processing Workshop |
Keywords | Field | DocType |
biomedical MRI,medical image processing,statistical testing,Akaike information criterion,FMRI activation detection,activated pixels,activation baseline pattern,functional MRI data analysis,parametric models,statistical test,voxels fMRI time series data,Activation Detection,Functional MRI,corrected Akaike information criterion | Voxel,Time series,Data modeling,Parametric model,Akaike information criterion,Experimental data,Pattern recognition,Computer science,Pixel,Artificial intelligence,Statistical hypothesis testing | Conference |
ISSN | ISBN | Citations |
pending E-ISBN : 978-1-4673-0181-7 | 978-1-4673-0181-7 | 2 |
PageRank | References | Authors |
0.37 | 4 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abd-Krim Seghouane | 1 | 78 | 12.27 |