Myelin Water Imaging is the technique of choice to measure myelination changes in healthy and abnormal situations in the brain. However, calculation of myelin water fraction (MWF) maps is challenging due to the low signal-to-noise ratio in the acquired data. Here, we demonstrate different filter methods, such as TGV, Gaussian and Wiener to overcome this problem. 3D GRASE images filtered with all three methods show significant enhanced fit-to-noise (FNR) values compared to unfiltered, while TGV preserves sharper edges and detailed structures. Finally, noise reduction and thus more reliable MWF maps can lead to certain advantages in the field of MS.