Title :
Rician Distributed FMRI: Asymptotic Power Analysis and Cramér–Rao Lower Bounds
Author :
Noh, Joonki ; Solo, Victor
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA
fDate :
3/1/2011 12:00:00 AM
Abstract :
Traditional functional MRI detection statistics for activation and hemodynamic response modeling assume Gaussian data, which is true only for high signal-to-noise ratio (SNR). The correct distribution is Rician. In this correspondence, we provide two new developments in the Rician case. First, a derivation of the theoretical asymptotic power function (as the number of samples goes to infinity). Second, the derivation of a Cramér-Rao lower bound. This allows a correct assessment of the impact of various signal and noise levels on detection power for activation and/or hemodynamic response parameter estimation accuracy. Based on our analysis, we are able to extend existing definitions of SNR by considering variation not only in baseline but also in drifts.
Keywords :
biomedical MRI; haemodynamics; medical image processing; medical signal detection; Cramer-Rao lower bounds; Rician case; Rician distributed FMRI; asymptotic power analysis; hemodynamic response parameter estimation accuracy; theoretical asymptotic power function; Activation detection; Rician distribution; SNR; fMRI; hemodynamic response modeling;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2010.2098400