Bayesian k-Space Estimation Decreases Image Noise and Increased Activation Detection

Oregon Convention Center 

In fMRI, as voxel sizes decrease, there is less material in them to produce a signal, leading to a decrease in the signal-to-noise ratio and contrast-to-noise ratio in each voxel. There have been many attempts to decrease the noise in an image in order to increase activation, but most lead to blurrier images. An alternative is to develop methods in spatial frequency space. Reducing noise in spatial frequency space has unique benefits. A Bayesian approach is proposed that quantifies available a priori information about spatial frequency coefficients, incorporates it with observed spatial frequency coefficients, and estimates spatial frequency coefficients values a posteriori. Inverse Fourier transform reconstructed images form marginal posterior mean estimated spatial frequency coefficients have reduced noise and increased detection power.

Bayesian

k-space

fmri

imaging 

Section on Bayesian Statistical Science