Partially adaptive STAP algorithm approaches to functional MRI.
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.
Huang
Lejian
L
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA. lejian@purdue.edu
Thompson
Elizabeth A
EA
Schmithorst
Vincent
V
Holland
Scott K
SK
Talavage
Thomas M
TM
D000465:Algorithms; D001921:Brain / Q000502:physiology; D001931:Brain Mapping; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D012372:ROC Curve; D015203:Reproducibility of Results; D013997:Time Factors