A grouping sparse coding (Group-SC) model is used in this study for the acceleration of myelin water content quantification. Images with improved quality are obtained using the Group-SC algorithm, in the aspect of minimal artefacts and good data consistency with fully-sampled labels. Myelin water fraction (MWF) maps reconstructed using Group-SC demonstrate more natural spatial distribution of myelin water in the brain. The proposed Group-SC algorithm has demonstrated its potential for the acceleration of the myelin water content quantification at R = 6.
This abstract and the presentation materials are available to members only; a login is required.