BOLD Susceptibility Map Reconstruction from fMRI by 3D Total Variation Regularization

Zikuan Chen¹, Arvind Caprihan¹, Vince Calhoun¹,²

In BOLD fMRI, the BOLD activity can be delineated in terms of susceptibility map reconstructed from BOLD complex image, which is a 3D ill-posed inverse problem involving 3D deconvolution and denosing. In this work, we report a solution by the split Bregman algorithm of total variation (TV) regularization, which is an iterative regularization (implemented by a 3-subproblems iteration) for image restoration from noisy blurred image. Numerical simulation and phantom experiment show that this novel TV technique outperforms the filter-truncated Fourier inverse solution.