An ideal classification of brain tissue structures as segmented gray matter (GM) has been a challenge while using standard T1-weighted image. One of the important ways of addressing this issue would be to use additional information from multispectral imaging such as T2- and T2-weighted FLAIR images. We evaluated the effect of multispectral segmentation on GM segmentation using SPM12 VBM and compared it with T1-only segmentation. We found that T1-segmentation overestimates dura, meninges and vessels as GM. This problem was successfully addressed by multispectral segmentation, which should be used as a segmentation model for future VBM studies.