Simulation of Myelin Water Imaging

Junyu Guo¹, Wilburn E. Reddick¹

Myelin water imaging is a promising, noninvasive technique for evaluating white matter diseases. Myelin water fraction (MWF) can serve as a direct indicator of myelin component change due to white matter diseases. To calculate MWF, the weighted regularized non-negative least squares (wrNNLS) algorithm with a large regularization coefficient was used to balance the sensitivity and reliability to measure MWF values. In this study, simulations were performed to compare the regularization of wrNNLS with the regularized non-negative least squares (rNNLS) algorithm and validate the large empirical selected regularization coefficient for wrNNLS due to imperfect refocusing pulses.