Digital human brain atlases consisting of MRI-based templates and semantic labels delineating different brain regions serve a critical role in neuroimaging, mainly facilitating spatial normalization and automated segmentation for the purposes of voxel-wise, region-of-interest, and network analyses.;Diffusion MRI templates contain rich information about the microstructure of the brain, however the accuracy of templates constructed based on the diffusion tensor imaging (DTI) model is limited in regions with complex neuronal microarchitecture. High angular resolution diffusion imaging (HARDI) overcomes limitations of the DTI model and is capable of resolving intravoxel heterogeneity. In this work a method to develop artifact-free HARDI template of the human brain from low angular resolution data is presented.;Existing white matter (WM) atlases have been generated either based on anatomical landmarks, thus mixing tracts with substantially different roles, or using DTI tractography, which fails in regions with crossing fibers. Connectivity-based atlases developed using HARDI templates and probabilistic tractography have potential to identify functionally distinct subregions of the brain. This work presents connectivity-based atlas of human brain WM created using HARDI template in ICBM-152 space and a set of FreeSurfer grey matter labels.
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