Name
Abstract | ||
|---|---|---|
Discriminating between active and non-active brain voxels in noisy functional magnetic resonance imaging (fMRI) data plays an important role when investigating task-related activations of the neuronal sites. A novel method for efficiently capturing drifts in the functional magnetic resonance imaging (fMRI) data is presented that leads to enhanced fMRI activation detection. The proposed algorithm apply a first order differencing to the fMRI time series samples in order to remove the drift effect. Using linear least-squares, a consistent hemodynamic response function (HRF) of the fMRI voxel is estimated as a first-step that leads to an optimal estimate of the drift based on a wavelet thresholding technique. The de-drifted fMRI voxel response is then obtained by removing the estimated drift from the fMRI time-series. Its performance is assessed using a visual task real fMRI data set. The application results reveal that the proposed method, which avoids the selection of a model to remove the drift component, leads to an improved activation detection performance in fMRI data. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/MLSP.2013.6661963 | Machine Learning for Signal Processing |
Keywords | Field | DocType |
biomedical MRI,difference equations,medical image processing,time series,HRF,activation detection performance,brain voxels,drift effect,drifts capturing method,fMRI activation detection,fMRI data,fMRI time series,fMRI voxel response,first order differencing,functional magnetic resonance imaging,hemodynamic response function,model-free optimal de-drifting,neuronal task-related activations,visual task real fMRI data set,wavelet thresholding technique,activation detection,consistent estimation,functional MRI,optimal de-drifting | Voxel,Computer vision,Functional magnetic resonance imaging,Pattern recognition,Wavelet thresholding,First order,Computer science,Artificial intelligence,Activation detection,Machine learning | Conference |
ISSN | Citations | PageRank |
1551-2541 | 3 | 0.41 |
References | Authors | |
14 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adnan Shah | 1 | 3 | 0.41 |
| Abd-Krim Seghouane | 2 | 78 | 12.27 |