Free For Non-Commercial Use Only Yes UNC, BIAS NITRC Mapping population-based structural connectomes Linux Yes Python, MATLAB, sh/bash Our developed PSC framework is a workflow which can simultaneously characterize a large number of white matter bundles within and across different subjects for group analysis. Given the DWI and T1 images it has three major components: (i) reliable construction of the structural connectome for the whole brain, including a robust tractography algorithm and streamline post-processing techniques, such as dilation of gray matter regions, streamline cutting, and outlier streamline removal are applied to improve the robustness of the extracted structural connectomes; (ii) low-dimensional representation of streamlines in each connection, including a shape analysis framework to separate the variation of streamlines in each cell of the streamlines, and an encoding and decoding procedure to ef´Čüciently compress the streamlines; (iii) multi-level connectome analysis, including the groupwise connectome analysis at three different levels, the streamline level, the weighted network level; and the binary network level. 2018-4-23 PSC1.0 Mapping population-based structural connectomes MR, Computational Neuroscience, Free For Non-Commercial Use Only, Python, MATLAB, sh/bash, NIfTI-1, Linux