We present a diffeomorphic diffusion tensor image (DTI) registration technique with multi-contrast images extracted from DTI and conventional structural MRI data. DTI provides microstructure information in white matter. However due to the acquisition protocols used in many clinical studies, DTI has lower SNR and spatial resolution compared to structural MRI. Complementary information can be used to improve the registration of white and gray matter. The proposed registration framework is constructed by a vector-valued large deformation diffeomorphic demons approach. Fractional anisotropy (FA) and eigenvalues are included as DTI components. T1-weighted image serves as the structural MRI component. The performance of the proposed method is compared with DTI only multi-contrast and full tensor based registration methods. Incorporation of structural data reduces FA variance in white matter adjacent to cortical regions. Compared to tensor based registration, the multi-contrast methods generate smaller shape variance but less directional consistency. We also demonstrate that the proposed method reduces fiber tract variations across individuals and creates a denser fiber tract probability map compared to DTI based registrations.