Name
Title | ||
|---|---|---|
Activation Points Extraction and Noise Removal of fMRI Signal using Novel Local Cosine Technique |
Abstract | ||
|---|---|---|
1 Abstract In this paper we report a novel procedure to accurately estimate the power spectrum of the noise in the fMRI signal at a given voxel location; the estimated power spectrum is used to determine the threshold used as shrinkage or soft threshold to remove noise from both 1-D and 2-D fMRI signal. Spatial processing, such as clustering is done on the entire signal to isolate the BOLD response and further investigate whether the new positions and numbers of the activation points are different from that of theoretically anticipated positions for the experiment performed. It is confirmed that the anticipated positions of the processed fMRI data and the actual positions of the activation points of the original fMRI data coincide as expected theoretically for the experiment performed. Keywords: fMRI, wavelet, noise, activation points, wiener filter |
Year | Venue | Keywords |
|---|---|---|
2007 | BIOCOMP | activation points,fmri,wiener filter,wavelet,noise,power spectrum |
Field | DocType | Citations |
Wiener filter,Trigonometric functions,Wiener deconvolution,Speech recognition,Gaussian noise,Noise removal,Mathematics | Conference | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Debebe Asefa | 1 | 1 | 1.08 |
| Dinesh P. Mital | 2 | 107 | 32.92 |
| Syed Haque | 3 | 23 | 11.48 |
| Shankar Srinivasan | 4 | 22 | 15.15 |