Name
Abstract | ||
|---|---|---|
In this paper, the architectures of three partially adaptive space-time adaptive processing (STAP) algorithms are introduced, one of which is explored in detail, that reduce dimensionality and improve tractability over fully adaptive STAP when used in the construction of brain activation maps in functional magnetic resonance imaging (fMRI). Computer simulations incorporating actual MRI noise and human data analysis indicate that element space partially adaptive STAP can attain close to the performance of fully adaptive STAP while significantly decreasing processing time and maximum memory requirements, and thus demonstrates potential in fMRI analysis. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TBME.2008.2006017 | IEEE Trans. Biomed. Engineering |
Keywords | Field | DocType |
image processing,functional magnetic resonance imaging (fmri),space-time adaptive processing (stap),neurophysiology,data analysis,fmri analysis,biomedical mri,human data analysis,functional magnetic resonance imaging,partially adaptive stap algorithm,element space partially adaptive stap,brain,brain activation maps,space-time adaptive processing,mri noise,adaptive space-time adaptive processing,medical image processing,algorithms,brain mapping,biomedical engineering,roc curve,magnetic resonance imaging,computer simulation,space time adaptive processing,adaptive filters,computer architecture | Brain mapping,Computer vision,Functional magnetic resonance imaging,Neurophysiology,Computer science,Brain activation,Algorithm,Image processing,Curse of dimensionality,Artificial intelligence,Adaptive filter,Space-time adaptive processing | Journal |
Volume | Issue | ISSN |
56 | 2 | 1558-2531 |
Citations | PageRank | References |
2 | 0.44 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lejian Huang | 1 | 11 | 1.79 |
| Elizabeth A. Thompson | 2 | 20 | 5.47 |
| Vincent J. Schmithorst | 3 | 100 | 9.51 |
| S. K. Holland | 4 | 69 | 10.21 |
| T M Talavage | 5 | 2 | 0.78 |