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Abstract #1627

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

Zikuan Chen1, Arvind Caprihan1, Vince Calhoun1,2

1Mind Research Network, Albuquerque, NM, United States; 2Electrical & Computer Engineering, University of New Mexico, Albuquerque, NM, United States

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.